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We investigated the benefit of a 6-week ambulant psychiatric rehabilitation program in an ambulant psychiatric rehabilitation clinic in Vienna, Austria, from January 2014 to December 2016 by an uncontrolled repeated measures study. The potential of this intervention program was assessed by effectiveness and cost measures using suitable statistical analyses. We compared the effectiveness and cost measures of this ambulant psychiatric rehabilitation program on patients for the period of up to 12 months after discharge to the period of 12 months before admission to the intervention program based on self-reported catamnesis questionnaires. For the program’s effectiveness measures, we accounted for both psychological indices for measuring depression severity, symptom burden, and functioning to document the health improvement of patients and economy-related indices such as the number of sick leave days for patients. For the program’s cost measures, both direct tangible treatment and medication costs and indirect tangible costs based on the productivity loss measured in non-working days of the patients were considered. The results significantly demonstrated that all psychological effectiveness measures for the patients highly improved by the 6-weeks rehabilitation program and remained rather stable 12 months after discharge. We found that costs for the 6-week ambulant psychiatric rehabilitation program could be easily covered within 12 months after discharge once a total societal cost perspective was considered. Even additional total cost savings of up to over 5000 Euro could be achieved which were highest for employed patients, followed by unemployed patients receiving rehabilitation allowance due to both their high direct medication and treatment costs as well as high indirect costs for productivity loss. The most important finding was that this treatment program was especially beneficial for rehabilitation patients in earlier stages of psychiatric diseases who were still employed, indicating the need for early intervention in mental disorder.

Multi-criterion decision-making models are widely used in supplier selection problems. This study contributes to a green supplier selection problem considering the green manufacturing, green transportation, and green procurement. This study contributes to reverse logistics, eco-design, reusing, recycling, and remanufacturing with their high impact on the industries. In addition to the logistics costs and transportation costs, the carbon emissions are considered. With regard to the game theory, this paper uses a cooperative green supplier selection model. If transportation requirements of two or more companies are combined, it will help manufacturers to have less \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${CO}_{2}$$\end{document}CO2 emissions with lower cost. After creating the optimization model to consider the uncertainty, this cooperative game theory model is established in a fuzzy environment. In this regard, a fuzzy rule-based (FRB) system is deployed and the set of fuzzy IF–THEN rules is considered. The proposed FRB model is contributed for the first time in the area of green supplier selection problem. Finally, some sensitivity analyses are conducted in a numerical example to evaluate the proposed model. With regard to the findings, although the cost of CO2 emission of horizontal cooperation is increased, the cost saving of companies is increased. It means our total cost is optimal in a logistic network using the cooperative game theory. The results also indicate that horizontal cooperation in logistic network causes less cost and benefits for each company. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-021-17015-2.

Aiming to assist the environmental sustainability of the Brazilian Amazonian agriculture, this article developed an eco-efficiency index, indicating the possible limits to maximize economic and environmental objectives, taking into account the best practices in the municipalities of the region. Shadow prices of degraded areas and forest preservation were also estimated using data envelopment analysis with directional distance functions. The results indicate that, on average, the analyzed municipalities are able to expand the production and the forest areas by 38% and reduce degraded areas and their inputs in the same proportion. The shadow prices allowed the estimation of the annual opportunity cost of the degraded areas and the preservation of the forest on the farms. The first, US$ 3,131,571, represented 0.04% of the annual output value, indicating that the internalization of that cost should be a low burden for the eco-efficient producer. The second, the total cost of preserving 80% of the area of property, represented US$ 120,890,662 or 1.7% of the annual income of the biome producers studied. Therefore, the main conclusion of this work is that the internalization of negative and positive externalities of agricultural production in the Amazonian biome does not make agricultural production economically unfeasible in the region. In addition, the reimbursement of damages avoided by carbon sequestration, through the Clean Development Mechanism (CDM) established by the Kyoto Conference, should further increase the economic and environmental sustainability of agriculture in the area.

Background Frailty is a common characteristic of patients undergoing transcatheter mitral valve repair (TMVR). It is unclear whether the physical vulnerability of frail patients translates into increased procedural health care utilization. Methods and results Frailty was assessed using the Fried criteria in 229 patients undergoing TMVR using the MitraClip system at our institution and associations with total costs and costs by cost centers within the hospital incurred during periprocedural hospitalization were examined. Frail patients (n = 107, 47%) compared to non-frail patients showed significantly higher total costs [median/interquartile range, excluding implant costs: 7,337 € (5,911–9,814) vs 6,238 € (5,584–7,499), p = 0.001], with a difference in means of 2,317 €. Frailty was the only clinical baseline characteristic with significant association with total costs. Higher total costs in frail patients were attributable primarily to longer stay on intermediate/intensive care unit (3.8 ± 5.7 days in frail vs 2.1 ± 1.7 days in non-frail, p = 0.003), but also to costs of clinical chemistry and physiotherapy. The prolonged stay on intermediate/intensive care unit in frail patients was attributable to postprocedural complications such as bleeding, kidney injury, infections and cardiovascular instability. Conclusion Frailty is associated with a mean 32% increase of hospital costs in patients undergoing TMVR, which is primarily the result of a prolonged recovery and increased vulnerability to complications. These findings are valuable for a hospital’s total cost calculation and resource allocation planning. Since frailty is regarded a potentially reversible health state, preventive interventions may help reduce costs in frail patients. Graphic abstract

The Plaintiff sued the Defendant for breach of a vessel repair contract for M.V. “KKG-2.” The total cost for the repairs was 1,076,078.75 USD. The Defendant initially paid 180,000 USD to the Plaintiff, and disputed its liability to pay the remaining 896,078.75 USD, arguing that the cost was excessive. The court rejected the Defendant’s evidence that the cost of repairs was excessive and found for the Plaintiff.

Background There is growing evidence that the cost for dementia care will increase rapidly in the coming years. Therefore, the objective of this paper was to determine the economic impact of treating clients with dementia in outpatient Dementia Service Centres (DSCs) and simulate the cost progression with real clinical and cost data. Methods To estimate the cost for dementia care, real administrative and clinical data from 1341 clients of the DSCs were used to approximate the total cost of non-pharmaceutical treatment and simulate the cost progression with a discrete-time Markov chain (DTMC) model. The economic simulation model takes severity and progression of dementia into account to display the cost development over a period of up to ten years. Results Based on the administrative data, the total cost for treating these 1341 clients of the DSCs came to 67,294,910 EUR in the first year. From these costs, 74% occurred as indirect costs. Within a five-year period, these costs will increase by 7.1-fold (16.2-fold over 10 years). Further, the DTMC shows that the greatest share of the cost increase derives from the sharp increase of people with severe dementia and that the cost of severe dementia prevails the cost in later periods. Conclusion The DTMC model has shown that the cost increase of dementia care is mostly driven by the indirect cost and the increase of severity of dementia within any given year. The DTMC reveals also that the cost for mild dementia will decrease steadily over the time period of the simulation, whereas the cost for severe dementia increases sharply after running the simulation for 3 years.

Municipal solid waste (MSW) management is among the essential tasks of municipalities that requires large amounts of fixed/variable and investment costs. In this system, the processes of collection and transportation include the major part of these costs. On the other hand, greenhouse gas (GHG) emission as environmental aspect and citizenship satisfaction as social aspect are also of particular importance, which are vital requirements for MSW management that need to be taken into account. In this study, a novel mixed-integer linear programming (MILP) model is developed to formulate the sustainable periodic capacitated arc routing problem (PCARP) for MSW management. The objectives are to concurrently minimize the total cost and total environmental emission, and maximize citizenship satisfaction. To solve the problem efficiently, a hybrid multi-objective optimization algorithm, namely, MOSA-MOIWOA is designed based on multi-objective simulated annealing algorithm (MOSA) and multi-objective invasive weed optimization algorithm (MOIWOA). To increase the algorithm performance, the Taguchi design method is employed to set the parameters optimally. The validation of the proposed methodology is evaluated using several problem instances in the literature. Finally, the obtained results demonstrate the high efficiency of the proposed model and algorithm to solve the problem.

Introduction Heart failure (HF) is a major public health concern, prevalent in millions of people worldwide. The most widely-used HF diagnostic method, echocardiography, incurs a decreased diagnostic accuracy for heart failure disease progression when patients are asymptomatic compared to those who are symptomatic. The purpose of this study is to conduct a cost-effectiveness analysis of heart failure diagnosis comparing echocardiography to a novel myocardial strain assessment (Fast-SENC), which utilizes cardiac-tagged magnetic resonance imaging. Methods We develop two models, one from the perspective of payers and one from the perspective of purchasers (hospitals). The payer model is a cost-effectiveness model composed of a 1-year short-term model and a lifetime horizon model. The hospital/purchaser model is a cost impact model where expected costs are calculated by multiplying cost estimates of each subcomponent by the accompanying probability. Results The payer model shows lower healthcare costs for Fast-SENC in comparison to ECHO ($24,647 vs. $39,097) and a lifetime savings of 37% when utilizing Fast-SENC. Similarly, the hospital model revealed that the total cost per HF patient visit is $184 for ECHO and $209 for Fast-SENC, which results in hospital contribution margins of $81 and $115, respectively. Conclusions Fast-SENC is associated with higher quality-adjusted life years and lower accumulated expected healthcare costs than echocardiogram patients. Fast-SENC also shows a significant short-term and lifetime cost-savings difference and a higher hospital contribution margin when compared to echocardiography. These results suggest that early discovery of heart failure with methods like Fast-SENC can be cost-effective when followed by the appropriate treatment. Electronic supplementary material The online version of this article (10.1186/s13561-019-0229-7) contains supplementary material, which is available to authorized users.

Rieber manufactures Gastronorm containers, commercial kitchen components, food transport and distribution equipment, aircraft water and waste tanks, refrigerators, sinks, etc. The company's core competencies are the deep drawing, annealing and welding of stainless steel. With a share of approx. 50%, material costs count significantly to company´s total costs.

This paper evaluates the impact of market competition on health care volume and cost. At the start of 2005, the financing system of Dutch hospitals started to be gradually changed from a closed-end budgeting system to a non-regulated price competitive prospective reimbursement system. The gradual implementation of price competition is a ‘natural experiment’ that provides a unique opportunity to analyze the effects of market competition on hospital behavior. We have access to a unique database, which contains hospital discharge data of diagnosis treatment combinations (DBCs) of individual patients, including detailed care activities. Difference-in-difference estimates show that the implementation of market-based competition leads to relatively lower total costs, production volume and number of activities overall. Difference-in-difference estimates on treatment level show that the average costs for outpatient DBCs decreased due to a decrease in the number of activities per DBC. The introduction of market competition led to an increase of average costs of inpatient DBCs. Since both volume and number of activities have not changed significantly, we conclude that the cost increase is likely the result of more expensive activities. A possible explanation for our finding is that hospitals look for possible efficiency improvements in predominantly outpatient care products that are relatively straightforward, using easily analyzable technologies. The effects of competition on average cost and the relative shares of inpatient and outpatient treatments on specialty level are significant but contrary for cardiology and orthopedics, suggesting that specialties react differently to competitive incentives.

The costs incurred for knee and hip arthroplasty depend on the different type of treatments provided within the chain of medical care. Indirect costs of the disease, such as the incapacity to work resulting from the underlying diseases and intangible costs which cannot be evaluated in monetary terms, must also be taken into account. Patient care is financed through established remuneration systems. According to different publications, data extrapolations have shown that German statutory health insurances spent approximately 1.4 to 1.6 billion euros per year on hospital treatments for hip arthroplasty between 2003 and 2009. With regard to knee arthroplasty, expenditure for the same period was estimated at 1.0 to 1.3 billion euros per year. The direct costs for the associated inpatient stays are financed through case-based fees, which are in turn based on the actual average hospital costs. The most commonly remunerated case fees (hip arthroplasty/knee arthroplasty) have shown cost increases of a few percentage points over the last few years which are mainly due to the rising costs of personnel. In the two case-fee groups, implant costs constitute 21 % of the total cost for hip treatments and 25 % of the total cost for knee treatments. Particularly complicated cases such as infected hip endoprostheses are relatively more costly. With regard to indirect costs, the diagnosis »Osteoarthritis of hip« (ICD-10 M16) resulted in 2,585,157 days of incapacity to work amongst compulsory statutory health insurees (excluding pensioners) in 2011. For »Osteoarthritis of knee« (ICD-10 M17) the figure was almost double at 4,971,052. Some patients who are in employment are unable to return to work despite having undergone a joint replacement and either have to change profession or accept a loss of income that includes social security contributions. Osteoarthritis, which is the most common reason for hip or knee replacements, is associated with a significant, increasing and in part immeasurable disease burden. International studies have demonstrated that the disease is accompanied by a high degree of suffering on the part of the patient as the large majority (70 % or more) would be personally willing to finance the hip or knee arthroplasty at their own cost if the procedures were not included amongst those reimbursed by health insurance systems. Hospitals in Germany finance the costs of arthroplasty with one of several possible arthroplasty case fees selected according to the specific service provided and the circumstances of each case. The case fees are based on the average costs of a given treatment. The case fee figures in 2015, which were based on certain benchmarks, ranged between approximately 6,400 euros and 17,300 euros. However, case fees do not always seem to cover the hospital costs, particularly in the treatment of more complicated cases.

Introduction Asthma is associated with a substantial economic burden on the German Statutory Health Insurance. Aims and objectives To determine costs and resource utilization associated with asthma and to analyze the impact of disease severity on subgroups based on age and gender. Methods A claims database analysis from the statutory health insurance perspective was conducted. Patients with an ICD-10-GM code of asthma were extracted from a 10 % sample of a large German sickness fund. Five controls for each asthma patient matched by age and gender were randomly selected from the same database. Costs and resource utilization were calculated for each individual in the asthma and control group. Incremental asthma-related costs were calculated as the mean cost difference. Based on prescribed asthma medication, patients were classified as intermittent or persistent. In addition, age groups of ≤5, 6–18, and >18 years were analyzed separately and gender differences were investigated. Results Overall, 49,668 individuals were included in the asthma group. On average, total annual costs per patient were €753 higher (p = 0.000) compared to the control group (€2,168 vs. €1,415). Asthma patients had significantly higher (p = 0.000) outpatient (€217), inpatient (€176), and pharmacy costs (€259). Incremental asthma-related total costs were higher for patients with persistent asthma compared to patients with intermittent asthma (€1,091 vs. €408). Women aged >18 years with persistent asthma had the highest difference in costs compared to their controls (€1,207; p p = 0.000). Conclusions The treatment of asthma is associated with an increased level of healthcare resource utilization and significantly higher healthcare costs. Asthma imposes a substantial economic burden on sickness funds.

The power-system structure is composed mainly of generation, transmission and distribution. This is also due to the unbundling process which takes place in many countries. Many power networks are unbundled commercially, with a separation of generation from the operation of the network. The power in a traditional power system is produced by a few large power plants located near primary energy sources (e.g., coal mines, water). The power is then transmitted at very high or high voltage for long distances (e.g., 500 km) and, finally, distributed to the end users. Generation is the main part of the power system. More than 50 % of the total costs of the power system are related to generation, which is also responsible for most of the polluting emissions. The general structure of the primary energy sources has changed during the last 30 years (see Fig. 1.2), but still fossil energy dominates the sources with a share of about 80 %.

This paper presents results of a case study in which a life cycle cost estimation tool has been developed and tested. Improving sustainability requires holistic information on the life cycle costs of the system. There is a need to increase the transparency of decision-making by informing customers about the costs of the solutions when taking into consideration the whole life cycle. This benefits both the supplier and the customer in forms of showing the total costs of the system and selecting the system with the lowest total costs.

Maintenance and repair of offshore wind turbines out at sea is expensive and can make up 25% of the total costs of a wind farm. Artificial intelligence and automatic self-organisation can significantly reduce these costs, according to the RAVE research project Methods and Tools for Proactive Maintenance of Offshore Wind Turbines. Up to now the maintenance and repair was mostly reactive, periodic or condition-dependent. If a repair is first triggered by a malfunction, it can be too late or too expensive; due to a lack of ships, spare parts or months of poor weather. The project gathered operating data for a broad range of malfunctions and breakdowns, and developed a proactive maintenance concept with automated recommendations for action combined with expected repair times and the remaining service life of components. In future the machines will be able to trigger maintenance measures themselves depending on resource allocation and available logistics.

The European buildings occupy a key place among the major energy consumer sectors, with high savings potential. The development of urban planning tools helpful to understand the right policy strategies turning the settled sustainable targets into real energy consumption savings is now a real challenge. Into this paper is described a methodology, for the mid-long term scenarios analysis, able to asses the buildings energy consumption of a municipality by means of a simulation approach and of a geo-referenced characterization of the stock. A thermal model, based on real consumption data, has been used to evaluate space heating energy demand; different savings opportunities have been simulated. Moreover, from the geo-referenced representation of the district heating network, through the integrated procedure, it is possible to perform the optimization of the network layout. A case study application in Turin is presented. Main results are the evaluation of energy consumptions, total costs of the interventions and the release of policy suggestions. Thanks to geo-referenced maps is allowed to put in evidence criticalities and policy effects through thematic maps. The methodology highlights the advantages of coupling a geographical information system application and energy demand forecasting model to build up a tool aimed at supporting decision-making.

This paper discusses the resource availability cost problem (RACP) with the objective of minimizing the total cost of the unlimited renewable resources by a prespecified project deadline. A tabued scatter search (TSS) algorithm is developed to solve the RACP. The deadline constraint is handled in coding. A tabu search module is embedded in the framework of scatter search. A computational experiment was conducted and the computational results show that the proposed TSS hybrid algorithm is effective and advantageous for the RACP.

In the last four decades, many studies have been conducted for least-cost and maximum-reliability design of water supply systems. Most models employed multi-objective genetic algorithm (e.g., non-dominated sorting genetic algorithm-II, NSGA-II) in order to explore trade-off relationship between the two objectives. This study proposes a reliability-based design model that minimizes total cost and maximizes seismic reliability. Here, seismic reliability is defined as the ratio of available demand to required water demand under earthquakes. Multi-objective Harmony Search Algorithm (MoHSA) is developed to efficiently search for the Pareto optimal solutions in the two objectives solution space and incorporated in the proposed reliability-based design model. The developed model is applied to a well-known benchmark network and the results are analyzed.

Background To evaluate the effects of a case management intervention for frail older people (aged 65+ years) by cost and utility. Materials and methods One hundred and fifty-three frail older people living at home were randomly assigned to either an intervention (n = 80) or a control group (n = 73). The 1-year intervention was carried out by nurses and physiotherapists working as case managers, who undertook home visits at least once a month. Differences in costs and quality-adjusted life years (QALYs) based on the health-related quality-of-life instruments EQ-5D and EQ-VAS, and also the incremental cost-effectiveness ratio were investigated. All analyses used the intention-to-treat principle. Results There were no significant differences between the intervention group and control group for total cost, EQ-5D-based QALY or EQ-VAS-based QALY for the 1-year study. Incremental cost-effectiveness ratio was not conducted because no significant differences were found for either EQ-5D- or EQ-VAS-based QALY, or costs. However, the intervention group had significantly lower levels of informal care and help with instrumental activities of daily living both as costs (€3,927 vs. €6,550, p = 0.037) and provided hours (200 vs. 333 hours per year, p = 0.037). Conclusions The intervention was cost neutral and does not seem to have affected health-related quality of life for the 1-year study, which may be because the follow-up period was too short. The intervention seems to have reduced hours and cost of informal care and help required with instrumental activities of daily living. This suggests that the intervention provides relief to informal caregivers.

With historical time series of 2001–2010, this paper uses the OSMM method to explore the cost of oil security in China. The cost can be divided into three parts according to the model: Transfer of wealth, potential loss of GDP and disruption loss. With the calculation, results are clear that the most content of the cost is wealth transfer, followed by disruption loss (or “MAC” for Macroeconomic Adjustment Cost) and potential GDP loss. Total cost of the oil can nearly make up to 4 % of the national GDP in the calculation.

This study aims at evaluating the economic effect of an e-ambulance project, or emergency telemedicine in the rural areas in Kochi Prefecture in Japan. Ambulances equipped with ICT devices which transmit images of acute patients to remote hospitals are focused on. Kochi Prefecture started an e-ambulance project in Aki and Muroto Cities in 2012. From two cities, it takes approximately one hour to reach emergency hospitals located in Kochi City, the prefectural capital. e-ambulance enhances wellness of residents, since they perceive more secure, and thus the CVM (Contingent valuation method) is applied and WTP (willingness to pay) is used as benefit and estimated based on surveys to residents, which amounts to 1,747 yen per resident per year. Total cost calculated is 381,792,228 yen over three years and accordingly, B/C ratio amounts 0.459. This study calculated another B/C ratio from the viewpoint of two local governments.

We consider a version of the Gale-Shapley stable matching setting, where each pair of nodes is associated with a (symmetric) matching cost and the preferences are determined with respect to these costs. This stable matching version is analyzed through the Price of Anarchy (PoA) and Price of Stability (PoS) lens under the objective of minimizing the total cost of matched nodes (for both the marriage and roommates variants). A simple example demonstrates that in the general case, the PoA and PoS are unbounded, hence we restrict our attention to metric costs. We use the notion of α-stability, where a pair of unmatched nodes defect only if both improve their costs by a factor greater than α ≥ 1. Our main result is an asymptotically tight trade-off, showing that with respect to α-stable matchings, the Price of Stability is \(\Theta \big( n^{\log ( 1 + \frac{1}{2 \alpha} )} \big)\). The proof is constructive: we present a simple algorithm that outputs an α-stable matching satisfying this bound.

Reordering buffer management (RBM) is an elegant theoretical model that captures the tradeoff between buffer size and switching costs for a variety of reordering/sequencing problems. In this problem, colored items arrive over time, and are placed in a buffer of size \(k\). When the buffer becomes full, an item must be removed from the buffer. A penalty cost is incurred each time the sequence of removed items switches colors. In the non-uniform cost model, there is a weight \(w_c\) associated with each color \(c\), and the cost of switching to color \(c\) is \(w_c\). The goal is to minimize the total cost of the output sequence, using the buffer to rearrange the input sequence.

We study the problem of assigning transmission ranges to radio stations placed in a d-dimensional (d-D) Euclidean space in order to achieve a strongly connected communication network with minimum total cost, where the cost of transmitting in range r is proportional to \(r^\alpha \). While this problem can be solved optimally in 1D, in higher dimensions it is known to be NP-hard for any \(\alpha \ge 1\).

The Green Value tool was developed in response to the need for simplified procedures that could be used in the field to conduct financial analysis for community-based forest enterprises (CFEs). Initially our efforts focused on a set of worksheets that could be used by both researchers and CFEs to monitor and analyze costs and income for one production period. The original worksheets were designed and tested for CFEs producing timber in Brazil. Since then, the worksheets have been further developed and incorporated into the Green Value tool, which includes a User’s Guide that leads users through a six-step financial analysis process and a facilitator’s guide for training workshops. In 2013, the tool was used to train 99 representatives of CFEs and organizations that support CFEs and to analyze a range of CFE products and production scales. The tool helps CFEsmonitor and analyze costs bymajor productive activity as well as administrative activities, and the results provided include the subtotal cost per activity and per type of input (labor, materials, machinery), total cost, average cost per unit sold, net income, and rate of return. These results are useful in helping CFEs to understand their costs, to identify ways to reduce costs or improve efficiencies, to evaluate scenarios, to provide transparent financial reporting to communities and donors, and to potentially secure finance. In addition, the results help inform policy makers and others working to support CFEs on the financial challenges CFEs face as well as the financial benefits they provide local communities through wages and purchases of materials and services.

This paper studies the vehicle routing optimization problem with uncertain demands and traveling time. Here two objectives are considered: (1) minimize the total cost of all vehicles, and (2) maximize the average service level for all customers. Based on the assumptions, a mathematical model is set up and then a particle swarm optimization algorithm is proposed to solve the model.

Current environmental issues are reflected in the environmental legislation of several countries. Because of the significance of environmental issues, enterprises actively seek ways in which to reduce CO2 emission across the logistics network Elhedhli and Merrick; Transp Res Part D 17(5):370–379, 2012. This paper develops a multi-objective fuzzy programming model for designing a strategic green logistics network under uncertainty, which aims to minimize the total cost and the CO2 emissions. Besides, to solve the multi-objective fuzzy model, an interactive fuzzy solution approach is applied. The case study indicates the applicability of the model and the usefulness of the solution method.

In the present paper the problem of reuse water networks (RWN) have been modeled and optimized by the application of a modified Particle Swarm Optimization (PSO) algorithm. A proposed modified PSO method lead with both discrete and continuous variables in Mixed Integer Non-Linear Programming (MINLP) formulation that represent the water allocation problems. Pinch Analysis concepts are used jointly with the improved PSO method. Two literature problems considering mono and multicomponent problems were solved with the developed systematic and results has shown excellent performance in the optimality of reuse water network synthesis based on the criterion of minimization of annual total cost.

In this paper, a mobility-aware Dual Pointer Forwarding scheme (mPF) is applied in Proxy Mobile IPv6 (PMIPv6) networks. When the MN moves, this scheme can reduce the high signalling overhead for intra-handoff/inter-handoff, because the Local Mobility Anchor (LMA) and Mobile Access Gateway (MAG) are connected by pointer chains. In other words, a handoff is aware of low mobility between the previously attached MAG (pMAG) and newly attached MAG (nMAG), and another handoff between the previously attached LMA (pLMA) and newly attached LMA (nLMA) is aware of high mobility. Based on these mobility-aware binding updates, the overhead of the packet delivery can be reduced. Also, the binding update cost and packet delivery cost for route optimization are analysed, based on the mathematical analytic model. Analytical results show that our mPF outperforms the PMIPv6 and the other pointer forwarding schemes, in terms of reducing the total cost of signalling.

How to careful formulate a scientific and reasonable preventive maintenance plan of the hospital’s high-value medical equipment is concerned to ensure the normal operation of medical equipment, and reduce the total cost of hospital operation management. The preventive maintenance of equipment has been widely used in traditional manufacturing. In China many General Hospitals also carry on preventive maintenance of medical equipment, but more consider the wear and failure disciplines of medical equipment to formulate preventive maintenance plan, and rarely consider the actual operation of the medical equipment. With the methods of preventive maintenance, this paper counts and analyzes the actual appointment amount of high-value medical equipment in radiology departments of West China Hospital, Sichuan University, and identifies appointment disciplines that governor the use disciplines of medical equipment. According to the use disciplines, the wear and failure disciplines of medical equipment, radiation department can careful formulate scientific and reasonable preventive maintenance plans of medical equipment and strategies. It is important to improve reliability and utilization of high-value medical equipment of radiology departments through the analysis of the appointment amount and combination with the wear and failure disciplines of medical equipment to formulate preventive maintenance plans.

Running a real estate business is risky; it requires heavy capital investment in land, professional training and recruitment. Nevertheless, this huge expenditure does not guarantee a great return, and it is possible to suffer a substantial loss if the entrepreneur makes a wrong decision. Provision of home fittings is one of the risks that the housing entrepreneur faces. Some buyers dislike the fittings and thus decide not to purchase the home. In Hong Kong, land supply is scarce, but demand is huge (7 million people live in a small city with a hilly landscape). Land price occupies a relatively large proportion of the costs in dwelling production. Provision of a towel ring, washing basin, water closet, and other fittings only uses a small proportion of the total costs of construction. Besides, many developers have run their business for years and accumulated sufficient knowledge on buyers’ taste. Nevertheless, in mainland China, especially in areas of low land costs, costs of fittings have become relatively high. The risk of supplying fittings that prospective owners dislike is higher. Many entrepreneurs do not wish to take the risk. This chapter aims at reviewing the asymmetric information and risks that housing entrepreneurs face in mainland China and analysing entrepreneurs’ decision in response to this risk.

Environmental issues and legislation pressures have forced the manufacturers to exert more effort in product recovery. This necessitates a production plan to take the product recovery and greenhouse gas emission into account. However, before doing so, a myth that re-using the recycled products would increase the total production cost or decrease the profit needs to be clarified. Therefore, in this study, we shall first show that a closed-loop production plan to consider both manufacture and remanufacture would be more economic and beneficial than a single activity of either manufacture or remanufacture. Second, when we conduct recycling activity in reality, how to estimate the amount of the recycled products to be re-utilized is another issue. In this study, the concept of the expected value transformed from a fuzzy recycling rate is adopted with intervals to describe its degree of uncertainty. Then, based on the periodic demands, a production plan for batch manufacture and remanufacture is proposed and analyzed in the form of a fuzzy mixed integer programming model (FMIP), such that the total costs of production cost, holding cost, emergency procurement cost, backlogging cost and the penalty for excessive carbon emission can be minimized with different degrees of satisfaction. A numerical example is presented to illustrate the validity of the model and the impact of recycling rate on the cost of such a close-loop production system for flexible applications.

As an inventory management model, VMI (Vendor Management Inventory) has gradually become the main way for dot-companies on the supply chain to improve their relationships between each other and the overall competitive advantages. Aiming at a two-level supply chain with demand uncertainty, this paper analyzes the impact of the VMI model on supply chain inventory management from the aspect of inventory control. The results show that the implementation of VMI model can effectively reduce the railway fastener inventory and the total cost of the supply chain.

Focused on the single distribution, vehicle routing problem with time windows (VRPTW) considered here is to achieve the minimization of total cost, which includes the travel costs and the penalty coefficient of time, under the constraints of time limits, volume, carrying capacity and variable cost. In order to solve this model, we choose an algorithm called Genetic Simulated Annealing algorithm (GSAA) with memory, and simulate this algorithm. The results showed that the approach to solve the VRPTW is very competitive.

Workshop facility layout is directly related to the reasonable flow of the logistics and information of the entire production system, which has a great impact on production capacity and safety. For multi-type and batch production systems, it is a critical and complex issue for research and investigation. The production mode of mass customization asks for the dynamic, multi-objective and multi-constraints specifications of the workshop facilities layout problem. In this study, a multi-objective dynamic optimization model is established based on three optimization objectives including the total cost (the materials handling cost and the rearrangement cost), non-logistics strength relationship and the required total area. In order to find Pareto solutions, an adaptive non-dominated sorting multi-objective genetic algorithm is designed for the specific model. Finally, a numerical example is applied to demonstrate that the proposed method is quite effective.

This paper discusses a multistage dynamic transportation allocation problem (DTAP) in a earth-rock transportation system under fuzzy environment, which is a multi-objective optimization process for minimizing total cost, duration and waste. Uncertain parameters are characterized as triangular fuzzy variables and fuzzy expected value concept is introduced to deal with the uncertainty. Dynamic programming particle swarm optimization algorithm (DP-based PSO) is developed to solve the above problem. Finally, the earth and rockfill dam construction in Pubugou Hydropower is used as a practical application example to demonstrate the practical application value of the optimization method, and the result is presented to highlight the newly developed innovation of the model and optimization algorithm.

The questions of environmental impact that company produce take important place nowadays. The ISO 14064-1 [1] standard specifies principles and requirements for monitor and control the greenhouse gas (GHG) emissions and removals. These requirements can be met by optimizing companies business processes (production, logistic, etc.) and by decreasing the power consumption of the companies’ equipments. As side effect of these changes, the total costs of companies can be decreased as well. Companies’ data centres and servers consume more than half of total spent electricity power. These servers are mostly used by companies’ software systems. Hence, if the software systems require less calculation time, less space, there will be no requirements to keep the big energy consuming servers, and the most of tasks can go in cloud as well. Hence, the environmental protection requirements should be considered in developing software systems for companies. In this paper, we aim to give some literature review and propose the research on the topic.

The situation we have looked at so far, where only one good is produced, plays a role in reality which is not to be underestimated because, like every economic theory, it too only really applies where the conditions are broadly met. For example, if a by-product is produced in addition to the main product and this provides only a small fraction of the revenue, we can then safely apply the theory of “single” supply. We therefore deduct the revenue of the by-product from total costs to perhaps achieve greater accuracy and regard the difference to be the principal product’s total costs.

We have already been introduced to the term “total costs” in the previous chapter and we know total costs are a definite, monotonically increasing function of the velocity of production. We would like to study this function a little more closely.

We consider a cutting problem, which have a practical application. In this problem, items are being cut from larger items, for example textile patterns from a panel of cloth. We deal steel tubes of given length, which have to be sawed from longer steel tubes. These longer steel tubes come with given costs and the sawing has to be planned such that the total costs are minimized.

We introduce FlowFlex, a highly generic and effective scheduler for flows of MapReduce jobs connected by precedence constraints. Such a flow can result, for example, from a single user-level Pig, Hive or Jaql query. Each flow is associated with an arbitrary function describing the cost incurred in completing the flow at a particular time. The overall objective is to minimize either the total cost (minisum) or the maximum cost (minimax) of the flows. Our contributions are both theoretical and practical. Theoretically, we advance the state of the art in malleable parallel scheduling with precedence constraints. We employ resource augmentation analysis to provide bicriteria approximation algorithms for both minisum and minimax objective functions. As corollaries, we obtain approximation algorithms for total weighted completion time (and thus average completion time and average stretch), and for maximum weighted completion time (and thus makespan and maximum stretch). Practically, the average case performance of the FlowFlex scheduler is excellent, significantly better than other approaches. Specifically, we demonstrate via extensive experiments the overall performance of FlowFlex relative to optimal and also relative to other, standard MapReduce scheduling schemes. All told, FlowFlex dramatically extends the capabilities of the earlier Flex scheduler for singleton MapReduce jobs while simultaneously providing a solid theoretical foundation for both.

In order to reduce the total costs, a minimum cost model (EOQ) was proposed based on the arrangement of explosive products supply support. Analyzing the whole flow including purchase, storage and transportation, explosive products were transported from military plants to depots and from depots to combat troops. Concerning all the constraints, the minimum cost model was transformed into mathematical programming model, and then optimal solutions can be solved. The model provides a theoretical basis to take measures to raise the efficiency of equipment support and improves the order capability in certain base.

This study was carried out within the framework of the Pacific Europe Network for Science and Technology (PACE-Net), a project funded by the European Commission (EC). The PACE-Net project seeks to improve regional and bi-regional collaboration and cooperation activities in science and technology (ST OCT—Overseas Countries and Territories). Its global aim is to develop networks between Pacific and European stakeholders from research entities, universities, and industries, and including policymakers, programme managers and civil society, in order to facilitate and establish balanced and multidisciplinary partnerships in priority areas of mutually beneficial research. Energy is the theme this study focuses on. Renewable research will be presented in comparison to other research themes in the Pacific. Furthermore, the renewable energy research institutions in the Pacific, their projects and the total cost of their research are discussed. It is seen that only 4 % of total research in the Pacific is on energy, and most collaboration is national. The percentage of energy research projects is compared to Pacific energy goals, and the funding/research/collaboration gap is discussed. The results are further divided into the categories ACP (Cook Islands, Federated States of Micronesia, Fiji, Kiribati, Marshall Islands, Nauru, Niue, Palau, Papua New Guinea, Solomon Islands, Timor-Leste, Tonga, Tuvalu, Samoa and Vanuatu), OCT (French Polynesia, New Caledonia, Pitcairn Islands, Wallis and Futuna) and regional organisations (University of the South Pacific, Secretariat of Pacific Community, South Pacific, Secretariat of the Pacific Regional Environment Programme) in the Pacific for specific data.

Large neighborhood search is a popular hybrid metaheuristic which results from the use of a complete technique—such as dynamic programming, constraint programming or MIP solvers—for finding the best neighbor within a large neighborhood of the incumbent solution. In this work we present an application of large neighborhood search to a strategic supply chain management problem from the Chemical industry, namely the configuration of a three-echelon hydrogen network for vehicle use with the goal of minimizing the total cost. Traditionally, these large-scale combinatorial optimization problems have been solved by means of mathematical programming techniques. Our experimental results show that large neighborhood search has the potential to be a viable alternative, especially when the complexity of the problem grows.

Adapter synthesis bridges incompatibilites between loosely coupled, stateful services. Formally, adapter synthesis reduces to partner synthesis. Beside an adapter, a partner could be a configurator or serve as an ingredient in solutions for discovery and substitution. We synthesize a cost-minimal partner for a given service based on additional behaviorial constraints. We consider the worst case total costs, specifying individual transition costs as natural numbers. In this paper, we sketch our formal approach, and briefly discuss our implementation.

The energy costs constitute a significant portion of the total cost of cloud providers. The major cloud data centers are often geographically distributed, and this brings an opportunity to minimize their energy cost. In this work, we model a geographically distributed data center network that is specialized to run batch jobs. Taking into account the spatio-temporal variation in the electricity prices and the outside weather temperature, we model the problem of minimizing the energy cost as a linear programming problem. We propose various heuristic solutions for the problem. Our simulations using real-life workload traces and electricity prices demonstrate that the proposed heuristics can considerably decrease the total energy cost of geographically distributed cloud data centers, compared to a baseline technique.

Cost calculation models are being improved continuously. The advanced methods of cost calculation use such techniques like activity-based costing or full cost allocation. These methods are based on the modelling of operation processes. This paper aims to introduce a new methodology of circuit diagrams by using the operational models as starting points. The operational models are improved through circuit models based on the morphotronic theory. In the circuit diagram profit objects are sources of activity fluxes that are consumed or dissipated inside the cost objects. The intensity of the fluxes is determined by the structure of the network. It consists of the profit objects and the cost objects that are connected with each other, furthermore, of the cost driver units (price or effort) that profit objects must pay and of the intensity of the bonds (resistances) or connections between economic objects (profit and cost objects). The circuit diagram computation of the flow computes in a way that the total cost of the system assumes the minimum value. The circuit diagram defines the independent fluxes and also how to compute the dependent fluxes by the superposition of the independent fluxes. The circuit diagram is included in a more general theory denoted morphotronic.

This paper describes modeling and simulation of a centralized supply chain distribution system for a single product in uncertain demand. A supply chain distribution system cost optimization model is developed in this concern, which includes multiple manufacturers, multiple distribution centers and multiple retailers. To provide a more realistic model structure, decision makers’ thinks that the distribution centers and retailers appears out of stock at the same time. With the MatLab 2010(a) carrying on the model, analyzing the influence which the order proportions and transportation cost in distribution centers and retailers to the supply chain distribution system total cost. As a result, on the one hand, when the order proportion is in the middle, the total cost is in the lowest level in supply chain distribution system. On the other hand, the order proportion is up and down, the total cost is no obvious change in supply chain distribution system. On the contrary, when the transportation cost usually is in the middle, the total cost is the lowest level in supply chain distribution system.