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Facility location problems in the plane are widely used tools of Operations Research in modeling real-world problems. In many of these problems restrictions have to be considered which correspond to regions in which a placement of new locations is forbidden. This paper investigates restrictions in 1-facility median problems in the plane. We introduce efficient algorithms for problems where the unrestricted problem can be solved in polynomial time. The algorithms are of a combinatorial nature and reduce the search for an optimal solution of the restricted problem to a finite number of candidates. The assumptions on the model are very weak. We only require that the forbidden area is a union of pairwise disjoint convex sets.

Developing a network of long-term care (LTC) services is currently a health policy priority in many countries, in particular in countries with a health system based on a National Health Service (NHS) structure. Developing such a network requires proper planning and basic information on future demand and utilization of LTC services. Unfortunately, this information is often not available and the development of methods to properly predict demand is therefore essential. The current study proposes a simulation model based on a Markov cycle tree structure to predict annual demand for LTC services so as to inform the planning of these services at the small-area level in the coming years. The simulation model is multiservice, as it allows for predicting the annual number of individuals in need of each type of LTC service (formal and informal home-based, ambulatory and institutional services), the resources/services that are required to satisfy those needs (informal caregivers, domiciliary visits, consultations and beds) and the associated costs. The model developed was validated using past data and key international figures and applied to Portugal at the Lisbon borough level for the 2010–2015 period. Given data imperfections and uncertainties related to predicting future LTC demand, uncertainty was modeled through an integrated approach that combines scenario analysis with probabilistic sensitivity analysis using Monte Carlo simulation. Results show that the model provides information critical for informing the planning and financing of LTC networks.

In Germany, "self-help friendliness" is an upcoming popular concept for the promotion of patient centredness through closer cooperation of health care services with self-help groups of chronically ill and/or disabled patients and their relatives. The study aimed at gathering information from physicians with special expertise in quality management on opportunities for and barriers against introducing more collaboration between physicians and self-help groups in outpatient care.A cross-sectional explorative survey was conducted with quality circle moderators (group leaders) from four German federal states in 2008 and 2010 (n=624 or 32.1% respondents out of 1943). Main outcome measure was the moderators' assessment of their peers, measured with 18 items. Statistical analyses were mainly descriptive, supplemented by subgroup analyses by federal state and characteristics of the respondents.Moderators see a large willingness of outpatient physicians to integrate self-help activities, and many opportunities for better cooperation with patient groups. Nevertheless, most types of cooperation need activation and motivation. To enhance the cooperation, additional fees by health insurance funds, CME credit points and the decrease of doctors' work load are most likely to be effective.Given the willingness of office-based physicians to cooperate with patient groups, increased patient centredness through cooperation seems to be an achievable quality target in medical practices in Germany. Self-help-friendliness in medical practices is considered as an important partnership approach; however, the implementation is still in the early stages and has to overcome diverse barriers, mainly based on unfavourable opinions, negative attitudes and lack of incentives.

Background Measuring change is fundamental to evaluations, health services research and quality management. To date, the Gold-Standard is the prospective assessment of pre- to postoperative change. However, this is not always possible (e.g. in emergencies). Instead a retrospective approach to the measurement of change is one alternative of potential validity. In this study, the Gold-Standard 'conventional' method was compared with two variations of the retrospective approach: a perceived-change design (model A) and a design that featured observed follow-up minus baseline recall (model B). Methods In a prospective longitudinal observational study of 185 hernia patients and 130 laparoscopic cholecystectomy patients (T0: 7-8 days pre-operative; T1: 14 days post-operative and T2: 6 months post-operative) changes in symptoms (Hernia: 9 Items, Cholecystectomy: 8 Items) were assessed at the three time points by patients and the conventional method was compared to the two alternatives. Comparisons were made regarding the percentage of missing values per questionnaire item, correlation between conventional and retrospective measurements, and the degree to which retrospective measures either over- or underestimated changes and time-dependent effects. Results Single item missing values in model A were more frequent than in model B (e.g. Hernia repair at T1: model A: 23.5%, model B: 7.9%. In all items and at both postoperative points of measurement, correlation of change between the conventional method and model B was higher than between the conventional method and model A. For both models A and B, correlation with the change calculated with the conventional method was higher at T1 than at T2. Compared to the conventional model both models A and B also overestimated symptom-change (i.e. improvement) with similar frequency, but the overestimation was higher in model A than in model B. In both models, overestimation was lower at T1 than at T2 and lower after hernia repair than after cholecystectomy. Conclusions The retrospective method of measuring change was associated with a larger improvement in symptoms than was the conventional method. Retrospective assessment of change results in a more optimistic evaluation of improvement by patients than does the conventional method (at least for hernia repair and laparoscopic cholecystectomy).

Die Bosch-Gruppe ist ein international fuhrendes Technologie- und Dienstleistungsunternehmen. Mit Kraftfahrzeug- und Industrietechnik sowie Gebrauchsgutern und Gebaudetechnik erwirtschafteten rund 275.000 Mitarbeiter im Geschaftsjahr 2009 einen Umsatz von 38,2 Mrd. €. Das Homburger Bosch-Werk gehort zum Geschaftsbereich Diesel Systems der Robert Bosch GmbH und produziert modernste Dieselkomponenten mittels komplexer Produktionsablaufe.

Introduction Clinical pathways (CPs) have been evaluated with regard to process optimization, economic effects, quality of care, patient satisfaction and staff satisfaction. IT- (information technology) supported CPs, integrated within the HIS (hospital information system), have been implemented in our department in 2004 for the first time world-wide. Herein, we describe the effect of this new concept on medical staff satisfaction. Methods A prospective anonymous and voluntary survey with standardized questionnaires was performed annually from 2006 until 2009 evaluating staff satisfaction concerning CPs. Questions comprised satisfaction with the software, staff's attitude towards CPs and the impact of CPs on work-related processes. Results Within the observation period the term “clinical pathways” became more common among doctors and nurses. Knowledge of the aims of CPs increased significantly in nursing staff (43.4–74.5%), whereas doctor's knowledge was on a constant high level. Standardization, process facilitation and cost effectiveness were the most claimed goals of CPs. Comprehensibility of the single steps within CPs was on a constant high level over the observation period. Generally, graphical layout and usability of CPs ranged on a very high satisfaction level. Acceptability of IT-supported CPs is independent from staffs computer knowledge. Conclusions Staff satisfaction with IT-supported CPs needs to take into account the job characteristics of the different professional groups. IT-supported CPs are leading to a high staff satisfaction, the aims of CPs are widely understood by medical employees. IT-supported CPs may ameliorate staff satisfaction and thereby enhance workflow efficiencies.

The problem discussed in this paper is motivated by the new recycling directive Waste Electrical and Electronic Equipment of the European Commission. The core of this law is, that each company which sells electrical or electronic equipment in a European country has the obligation to recollect and recycle an amount of returned items which is proportional to its market share. To assign collection stations to companies, in Germany for one product type a territory design approach is planned. However, in contrast to classical territory design, the territories should be geographically as dispersed as possible to avoid that a company, respectively its logistics provider responsible for the recollection, gains a monopoly in some region. First, we identify an appropriate measure for the dispersion of a territory. Afterwards, we present a first mathematical programming model for this new problem as well as a solution method based on the Greedy Randomized Adaptive Search Procedure methodology. Extensive computational results illustrate the suitability of the model and assess the effectiveness of the heuristic.

To model flexible objectives for discrete location problems, ordered median functions can be applied. These functions multiply a weight to the cost of fulfilling the demand of a customer which depends on the position of that cost relative to the costs of fulfilling the demand of the other customers. In this paper a reformulated and more compact version of a covering model for the discrete ordered median problem (DOMP) is considered. It is shown that by using this reformulation better solution times can be obtained. This is especially true for some objectives that are often employed in location theory. In addition, the covering model is extended so that ordered median functions with negative weights are feasible as well. This type of modeling weights has not been treated in the literature on the DOMP before. We show that several discrete location problems with equity objectives are particular cases of this model. As a result, a mixed-integer linear model for this type of problems is obtained for the first time.

In this paper, we analyze flexible models for capacitated discrete location problems with setup costs. We introduce a major extension with regards to standard models which consists of distinguishing three different points of view of a location problem in a logistics system. We develop mathematical programming formulations for these models using discrete ordered objective functions with some new features. We report on the computational behavior of these formulations tested on a randomly generated battery of instances.

To improve processes in hospitals, a case study was conducted at a German university hospital, which consists of more than 30 clinics and institutes on a large campus. The case study focused on the analysis of the patient flow and of machine utilization in the radiology department. Radiological devices are spread over the campus and located in different buildings. Patients with restricted mobility have to be transported by a vehicle transportation service across the campus. However, a vehicle transport can considerably influence the patients' punctual arrival to their appointments. The observations of the case study showed that the current organization of the radiology department results in high patient waiting times and machine idle times. The university hospital is planning to conduct significant organizational changes, especially with regard to the organization of the radiology department. This case study was conducted to support the planning processes of the clinic and to reveal and estimate optimization potential. To analyze the patient flow, a discrete event multicriteria simulation model was designed and implemented. By modeling different scenarios, it was possible to easily compare and assess distinct alternatives. This led to improved machine utilization and reduced waiting times.

Objectives Since 2004 a large German health insurance company (Techniker Krankenkasse) has provided integrated inpatient health care (IHC) contracts to its members. The aim of the study was to evaluate the effects of this programme on patient satisfaction and health-related quality of life among heart disease patients. Methods A case–control study was conducted with patients in cardiologic and cardiosurgical units who were discharged in 2006. The cases included approximately 750 IHC patients from eight hospitals, whereas the controls were chosen both from the same and other hospitals. Data consisted of interviews in written form (overall response rate: 70.7%), and routine data of health insurances. Main assessment criteria were patient satisfaction with care measured by a modified standardised questionnaire (FK-P), and the SF-12 instrument for measuring health-related quality of life. Results In many respects, patient satisfaction with care was the highest among the IHC patients, followed by controls from the same hospitals, and by those from other hospitals. The process indicator of the lowest satisfaction across all three groups was the provision of competencies to deal with problems at home after discharge (“patient education”). Further benefits of IHC are the reduction of both the average length of hospital stay and the waiting time of patients for rehabilitation. By contrast, no statistically significant differences were found with regard to patient-reported health improvement and health-related quality of life. Conclusions Although the IHC programme did not seem to improve the patients’ health-related quality of life and health status, positive effects on patient satisfaction and the efficiency of hospital care could be detected. For future research one ought to check the advantages and/or disadvantages of IHC for other disease groups, and should, if possible, use a prospective study design as well as integrate clinical parameters.

In this paper we develop a network location model that combines the characteristics of ordered median and gradual cover models resulting in the Ordered Gradual Covering Location Problem (OGCLP). The Gradual Cover Location Problem (GCLP) was specifically designed to extend the basic cover objective to capture sensitivity with respect to absolute travel distance. Ordered Median Location problems are a generalization of most of the classical locations problems like p-median or p-center problems. They can be modeled by using so-called ordered median functions. These functions multiply a weight to the cost of fulfilling the demand of a customer which depends on the position of that cost relative to the costs of fulfilling the demand of the other customers. We derive Finite Dominating Sets (FDS) for the one facility case of the OGCLP. Moreover, we present efficient algorithms for determining the FDS and also discuss the conditional case where a certain number of facilities are already assumed to exist and one new facility is to be added. For the multi-facility case we are able to identify a finite set of potential facility locations a priori, which essentially converts the network location model into its discrete counterpart. For the multi-facility discrete OGCLP we discuss several Integer Programming formulations and give computational results.

We consider a fault tolerance version of the Uncapacitated Facility Location Problem with User Preferences. As a consequence, our problem, which we wish to name the Uncapacitated Facility Location Problem with user preferences and q-level of reliability (q-level UFLPP), is much more difficult to solve. A computational study shows the advantages and difficulties of this approach.

Acceptance sampling is one important part of logistic processes and production. Because of that, we developed a new model, named DMGI (Dynamic Mixed Goods Inspection) which uses past inspections in order to support companies deciding which delivery should be inspected in goods income.

In the last two decades, among the large amount of literature available on Hub Location Problems (HLP), applications in Public Transport (PT) have received less attentions compared to other fields, for example telecommunications. The first mathematical model for HLPs is proposed by O’Kelly [5] in 1987. In a HLP network, the flow originated from an origin i and destinated to node j is not shipped directly, rather, it is sent via some selected intermediate nodes (called hub nodes) and maybe intermediate edges (called hub edges) connecting these hubs. The sub-network composed of these hub facilities is known as hub-level network. The remaining nodes and edges are called spoke nodes or spoke edges of the spoke-level network. For applications in public transport planning, the hub level network consists of special types of transportation facilities which may be fast-lines, etc. Fig. 1 depicts a simple hub location model applied to public transport planning.

In this paper, we deal with a facility location problem where we build new facilities or close down already existing facilities at two different distribution levels over a given time horizon. In addition, we allow to carry over stock in warehouses between consecutive periods. Our model intends to minimize the total costs, including transportation and inventory holding costs for products as well as fixed and operating costs for facilities. After formulating the problem, we propose a Lagrangian approach which relaxes the constraints connecting the distribution levels. A procedure is developed to solve the resulting, independent subproblems and, based on this solution, to construct a feasible solution for the original problem.

The project aimed at testing the feasibility of a quality improvement system based on patient-reported outcomes in short-stay surgery for cholecystectomy. In two centers for short-stay surgery, patients referred for laparoscopic cholecystectomy were surveyed between Aug 1999 and Jan 2002. Patients reported on health-related quality of life (SF-36), symptoms (gallstone symptom checklist, GSCL) and other indicators preoperatively (T0), 14 days (T1) and 6 months postoperatively (T2). The SF-36 subscales physical functioning, bodily pain, and role physical as well as the GSCL and treatment satisfaction at T2 were considered as main outcomes. The main outcomes were analyzed by generalized linear models with regard to predictors. At T0 a total of 205 patients were included. The response rate at T2 was 63.4% (74.6% females, 53.6 years of age). The GSCL score at T0 (29.4% preoperatively) fell slightly to 27.9% at T1 and decreased to 14.8% at T2 (T0–T2: p

Although the maximization of health is a key objective in health care systems, location-allocation literature has not yet considered this dimension. This study proposes a multi-objective stochastic mathematical programming approach to support the planning of a multi-service network of long-term care (LTC), both in terms of services location and capacity planning. This approach is based on a mixed integer linear programming model with two objectives – the maximization of expected health gains and the minimization of expected costs – with satisficing levels in several dimensions of equity – namely, equity of access, equity of utilization, socioeconomic equity and geographical equity – being imposed as constraints. The augmented ε-constraint method is used to explore the trade-off between these conflicting objectives, with uncertainty in the demand and delivery of care being accounted for. The model is applied to analyze the (re)organization of the LTC network currently operating in the Great Lisbon region in Portugal for the 2014-2016 period. Results show that extending the network of LTC is a cost-effective investment.

A novel heuristic approach is proposed for solving a large scale facility location problem arising in supply chain design. The problem formulation includes many practical aspects such as a dynamic planning horizon, generic supply chain structure, inventory and distribution of goods, budget constraints, and storage limitations. Moreover, facility location decisions are modelled through the gradual relocation of existing facilities to new sites over a given planning horizon. The heuristic approach explores the solution of the linear relaxation of the problem. It successively rounds the fractional variables corresponding to the 0/1 decisions of changing the facilities’ status (i.e., open new / close existing facilities), and it is also used to roughly estimate the total number of facility configuration changes over the planning horizon. The proposed heuristic performs very well on a large set of randomly generated problems, producing feasible solutions that on average only deviate 1.4% from the optimum.

This paper analyzes and solves a patient transportation problem arising in several large hospitals. The aim is to provide an efficient and timely transport service to patients between several locations on a hospital campus. Transportation requests arrive in a dynamic fashion and the solution methodology must therefore be capable of quickly inserting new requests in the current vehicle routes. Contrary to standard dial-a-ride problems, the problem under study contains several complicating constraints which are specific to a hospital context. The paper provides a detailed description of the problem and proposes a two-phase heuristic procedure capable of handling its many features. In the first phase a simple insertion scheme is used to generate a feasible solution, which is improved in the second phase with a tabu search algorithm. The heuristic procedure was extensively tested on real data provided by a German hospital. Results show that the algorithm is capable of handling the dynamic aspect of the problem and of providing high quality solutions. In particular, it succeeded in reducing waiting times for patients while using fewer vehicles.

Diese Arbeit befasst sich mit strategischen Entscheidungen im Bereich des Supply-Chain-Managements. Dabei wird ein allgemeines mathematisches Optimierungsmodell zur Standortplanung vorgestellt. Das Modell ist dynamisch und kapazitatsbeschrankt; es kann auf mehrere Produkte und Ebenen angewendet werden und berucksichtigt externe Materialbeschaffung, Produktions-, Vertriebs- und Lagerentscheidungen, Sicherheitsbestande, Budgetrestriktionen und Kapazitatsverlegungen. Um die Nachfrage moglichst kostenminimal zu decken, werden Kapazitatserweiterungen bzw.-reduzierungen betrachtet. Das formale Modell wird auf ein Beispiel aus der Stahlindustrie angewendet, wobei die Praxistauglichkeit des Modells analysiert wird. Alle Berechnungen erfolgen mit Hilfe des Optimierungstools XPressMP (Dash Optimization 2004).

We consider the problem of planning inspections and other tasks within a software development (SD) project with respect to the objectives quality (no. of defects), project duration, and costs. The considered model of SD processes comprises the phases of coding, inspection, test, and rework and includes assigning tasks to persons and generating a project schedule. Based on this model we discuss a multiobjective optimisation problem. For solving the problem (i.e., finding an approximation of the efficient set) we develop a multiobjective evolutionary algorithm. Details of the algorithm are discussed as well as results of its application to sample problems.

In this chapter, we provide a broad overview of the most representative multicriteria location problems as well as of the most relevant achievements in this field, indicating the relationship between them whenever possible. We consider a large number of references which have been classified in three sections depending on the type of decision space where the analyzed models are stated. Therefore, we distinguish between continuous, network, and discrete multicriteria location problems.

In this paper, we consider the problem of planning inspections and other operations within a software development (SD) project with respect to the objectives quality (no. of defects), project makespan, and costs. The considered model of SD processes comprises the phases coding, inspection, test, and rework and includes the assignment of operations to persons and the generation of a project schedule. Based on this model we discuss a multiobjective optimization problem. For solving the problem (i.e. finding an approximation of the efficient set) we develop a multiobjective evolutionary algorithm. Details of the algorithm are discussed as well as results of its application to sample problems.

Das Gesundheitsamt Hamburg-Eimsbuttel initiierte 2005 in der sozial benachteiligten Lenzsiedlung ein Praventionsprogramm, das mit dem Runden Tisch „Lenzgesund“ und weiteren Koopera­tionspartnern unter der Federfuhrung des Gesundheitsamtes umgesetzt wurde. Diesen Umsetzungsprozess unterstutzte das Institut fur Medizinische Soziologie, Sozialmedizin und Gesundheitsokonomie im Rahmen einer Langzeit-Evalua­tion mit unterschiedlichen quantitativen und qualitativen, zum Teil neu entwickelten Methoden der Berichterstattung und Evaluation sowie einem innova­tiven deutschsprachigen Instrument zur Messung von „Kapazitatsentwicklung im Quartier“ (KEQ).

We present two heuristic methods for solving the Discrete Ordered Median Problem (DOMP), for which no such approaches have been developed so far. The DOMP generalizes classical discrete facility location problems, such as the p-median, p-center and Uncapacitated Facility Location problems. The first procedure proposed in this paper is based on a genetic algorithm developed by Moreno Vega [MV96] for p-median and p-center problems. Additionally, a second heuristic approach based on the Variable Neighborhood Search metaheuristic (VNS) proposed by Hansen & Mladenovic [HM97] for the p-median problem is described. An extensive numerical study is presented to show the efficiency of both heuristics and compare them.

The Discrete Ordered Median Problem (DOMP) generalizes classical discrete location problems, such as the N-median, N-center and Uncapacitated Facility Location problems. It was introduced by Nickel [S. Nickel. Discrete Ordered Weber problems. In B. Fleischmann, R. Lasch, U. Derigs, W. Domschke, and U. Rieder, editors, Operations Research Proceedings 2000, pages 71–76. Springer, 2001], who formulated it as both a nonlinear and a linear integer program. We propose an alternative integer linear programming formulation for the DOMP, discuss relationships between both integer linear programming formulations, and show how properties of optimal solutions can be used to strengthen these formulations. Moreover, we present a specific branch and bound procedure to solve the DOMP more efficiently. We test the integer linear programming formulations and this branch and bound method computationally on randomly generated test problems. Ministerio de Ciencia y Tecnología

Let A be a nonempty finite subset of the plane representing the geographical coordinates of a set of demand points (towns, …), to be served by a facility, whose location within a given region S is sought. Assuming that the unit cost for a∈A if the facility is located at x∈S is proportional to dist(x,a) — the distance from x to a — and that demand of point a is given by ωa, minimizing the total transportation cost TC(ω,x) amounts to solving the Weber problem. In practice, it may be the case, however, that the demand vector ω is not known, and only an estimator ωcirc; can be provided. Moreover the errors in such estimation process may be non-negligible. We propose a new model for this situation: select a threshold value B>0 representing the highest admissible transportation cost. Define the robustness ρ of a location x as the minimum increase in demand needed to become inadmissible, i.e. ρ(x)=min{|ω−ωcirc;|:TC(ω,x)>B,ω≥0} and find the x maximizing ρ to get the most robust location. Ministerio de Ciencia y Tecnología Deutsche Forschungsgemeinschaft

Although facility location and configuration of global manufacturing and distribution networks have been studied formany years, a number of important real world issues has not received adequate attention in the literature. In this paper we propose realistic models for the strategic planning and design of global supply chains. Our main concern is to provide comprehensive models which explicitly capture the essential elements of many industrial environments. A generic mathematical programming model is described in detail which became part of Supply Chain Design, a module within mySApTM Supply Chain Management, developed by SAPAG. Moreover, extensions to the dynamic situation are discussed.

Planning sales territories may be viewed as the problem of grouping small geographic sales coverage units (e.g. counties, zip code areas, company trading areas) into larger geographic clusters called sales territories in such a way that the latter are acceptable according to managerially relevant criteria (e.g. minimal/maximal/average sales potentials or travel times). In contrast to the currently available set-partitioning oriented models, we propose a facility location approach for planning sales territories. The integer programming formulation we developed for this approach is a discrete capacitated m-median problem with the additional requirement that sales territories have to be connected. As this problem is NP-hard, we devised an efficient, interchange based heuristic procedure for solving large scale problems. The algorithms are embedded in the so-called BusinessManager, a software tool developed by Geomer GmbH, Germany.

Organizations that develop software have recognized that software process models are particularly useful for maintaining a high standard of quality. In the last decade, simulations of software processes were used in several settings and environments. This paper gives a short overview of the benefits of software process simulation and describes the development of a discrete-event model, a technique rarely used before in that field. The model introduced in this paper captures the behavior of a detailed code inspection process. It aims at reducing the risks inherent in implementing inspection processes and techniques in the overall development process. The determination of the underlying cause-effect relations using data mining techniques and empirical data is explained. Finally, the paper gives an outlook on our future work.

In a recent series of papers a new type of objective function in location theory, called ordered median function, has been introduced and analyzed. This objective function unifies and generalizes most common objective functions used in location theory. In this paper we identify finite dominating sets for these models and develop polynomial time algorithms together with a detailed complexity analysis.

Whenever a social institution plans new buildings or a modification of buildings (e.g. a hospital or a nursing home) the question arises how to arrange the rooms and functional units. One criterion is certainly the total walking distance of staff members, patients/clients and visitors.

Petroleum industry plays a vital role in the modern global economy, owing to the fact that it is the largest source of energy in the world. Design and planning of the oilfield developments have become crucial concerns of the oil industry managers. In addition, crude oil transportation plays a critical role in the global supply chain of oil industry. In this work, we develop a model to design the oilfield development and plan crude oil transportation problems. A mixed integer model is proposed to extend the classical facility location-allocation problems by several features. Additionally, the model supports the selection of the transportation system and the planning of pipeline networks installations. This work ends with two sensitivity analyses. Two one-factor-at-a-time sensitivity analyses have been done with respect to the length of the planning horizon and the number of potential wells.