22 results on '"Hamed Kazemipoor"'
Search Results
2. A bi-objective aircraft maintenance routing problem based on flying hours to efficient use of available fleet
- Author
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Hiwa Esmaeilzadeh, Alireza Rashidi Komijan, Hamed Kazemipoor, Mohammad Fallah, and Reza Tavakkoli-Moghaddam
- Subjects
Management of Technology and Innovation ,Strategy and Management ,Business and International Management - Abstract
Purpose The proposed model aims to consider the flying hours as a criterion to initiate maintenance operation. Based on this condition, aircraft must be checked before flying hours threshold is met. After receiving maintenance service, the model ignores previous flying hours and the aircraft can keep on flying until the threshold value is reached again. Moreover, the model considers aircraft age and efficiency to assign them to flights. Design/methodology/approach The aircraft maintenance routing problem (AMRP), as one of the most important problems in the aviation industry, determines the optimal route for each aircraft along with meeting maintenance requirements. This paper presents a bi-objective mixed-integer programming model for AMRP in which several criteria such as aircraft efficiency and ferrying flights are considered. Findings As the solution approaches, epsilon-constraint method and a non-dominated sorting genetic algorithm (NSGA-II), including a new initializing algorithm, are used. To verify the efficiency of NSGA-II, 31 test problems in different scales are solved using NSGA-II and GAMS. The results show that the optimality gap in NSGA-II is less than 0.06%. Finally, the model was solved based on real data of American Eagle Airlines extracted from Kaggle datasets. Originality/value The authors confirm that it is an original paper, has not been published elsewhere and is not currently under consideration of any other journal.
- Published
- 2022
3. Providing a model for the issue of multi-period ambulance location
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Mohadese Aghabozorgi, Agnieszka Szmelter-Jarosz, Hamed Kazemipoor, and Mohammad Ebrahim Sadeghi
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General Economics (econ.GN) ,Mathematical model ,Operations research ,Computer science ,Multi period ,media_common.quotation_subject ,Ambulance Location ,Response time ,Transportation theory ,Time Slots ,Stochastic Demand ,FOS: Economics and business ,Geographical zone ,Transfer (computing) ,Ambulance Transfer ,Function (engineering) ,Assignment problem ,media_common ,Economics - General Economics - Abstract
In this study, two mathematical models have been developed for assigning emergency vehicles, namely ambulances, to geographical areas. The first model, which is based on the assignment problem, the ambulance transfer (moving ambulances) between locations has not been considered. As ambulance transfer can improve system efficiency by decreasing the response time as well as operational cost, we consider this in the second model, which is based on the transportation problem. Both models assume that the demand of all geographical locations must be met. The major contributions of this study are: ambulance transfer between locations, day split into several time slots, and demand distribution of the geographical zone. To the best of our knowledge the first two have not been studied before. These extensions allow us to have a more realistic model of the real-world operation. Although, in previous studies, maximizing coverage has been the main objective of the goal, here, minimizing operating costs is a function of the main objective, because we have assumed that the demand of all geographical areas must be met., International Journal of Innovation in Engineering (IJIE), 2021
- Published
- 2022
4. Big data analysis of IoT-based supply chain management considering FMCG industries
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Hamed Kazemipoor, Mohammad Fallah, Seyed Esmaeil Najafi, and Hamed Nozari
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Economics and Econometrics ,Supply chain management ,Computer science ,business.industry ,Process (engineering) ,Supply chain ,media_common.quotation_subject ,05 social sciences ,Big data ,02 engineering and technology ,Management Information Systems ,Risk analysis (engineering) ,Management of Technology and Innovation ,0502 economics and business ,Sustainability ,Information technology management ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Quality (business) ,Business and International Management ,business ,Productivity ,050203 business & management ,Information Systems ,media_common - Abstract
Supply chain is one of the main pillars of manufacturing and industrial companies whose smartness can help business to be intelligent. To this end, the use of innovative technologies to make it smart is always a concern. The smart supply chain utilizes innovative tools to enhance quality, improve performance and facilitate the decision-making process. Internet of things (IoT) is one of the key components of the IT infrastructure for the development of smart supply chains that have high potential for creating sustainability in systems. Furthermore, IoT is one of the most important sources of big data generation. Big data and strategies for data analysis as a deep and powerful solution for optimizing decisions and increasing productivity are growing rapidly. For this reason, this paper attempts to examine informative supply chain development strategies by investigating the supply chain in FMCG industries as a special case and to provide a complete analytical framework for building a sustainable smart supply chain using IoT-based big data analytics. The proposed framework is based on the IoT implementation methodology, with emphasis on the use of input big data and expert reviews. Given the nature of the FMCG industry, this can lead to better production decisions.
- Published
- 2021
5. Solve a New Robust Bi-Objective Model for Designing Blood Supply Chain Network by NSGA II and Imperialist Competitive Algorithm
- Author
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Melika Ghanbarzadeh and Hamed Kazemipoor
- Subjects
Mathematical optimization ,Sorting algorithm ,Computer science ,robust planning ,Supply chain ,blood supply chain ,Imperialist competitive algorithm ,multi-objective genetic algorithm ,Product (business) ,Chain (algebraic topology) ,Perishability ,Sensitivity (control systems) ,integer programming ,Integer programming - Abstract
In this supply chain, blood and blood products are investigated as a product from donor to patient. Specific characteristics of blood supply chain such as perishability and existence of uncertainty in the structure of this chain have caused problems for planning in this regard. However, this point should be considered that the importance of this supply chain cannot be compared to perishable products. Life and death issue of this product is the main difference between blood and other perishable products. Therefore, a comprehensive model was presented in this study to locate blood bank components within a network and to determine the allocation of these components considering blood donation centers, blood testing and processing laboratories, distribution centers or blood banks, and demand centers. Since designing supply chain and locating issues at large dimensions are NP-hard, the suggested models at small sizes were compared using the exact method (GAMS), non-dominated genetic sorting algorithm, and multi-objective imperialist competitive algorithm. The results were compared with GAMS. This shows normal performance of the proposed algorithms and led to using these two algorithms at average and large sizes for research questions. Also, by analyzing sensitivity on important parameters, important managerial findings are suggested for similar conditions.
- Published
- 2021
6. Development of Integrated Multi-objective Green Supply Chain Scheduling Model: Production, Distribution and Heterogeneous Vehicle Routing with Customer Time Windows
- Author
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Maliheh Ganji, hamed kazemipoor, Seyyed Mohammad Hadji Molana, and Seyed Mojtaba Sajadi
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production scheduling ,batch delivery ,multi-objective meta-algorithm ,Management. Industrial management ,heterogeneous vehicle routing ,time window ,integrated production and distribution problem ,HD28-70 - Abstract
Objective: In this study, different ways of delivering goods to customers are created and therefore the vehicle routing decisions are added to this issue. In this case, customers must be divided into clusters and each customer assigned to one means of transportation in order to minimize the cost of orders between customers. In this study, the problem of integrated supply chain scheduling is determined by timely delivery of orders, scheduling orders on a machine in a manufacturing system and batch shipment, allocation to multiple heterogeneous transport modes according to capacity, and finally order delivery. To customers in the time window, it aims to minimize the total cost of distributing orders and the constant and variable costs of fuel and carbon emissions of the vehicle and the total time delay of customer orders. Methods: The problem programming model is a mathematical model of complex nonlinear integer and has been used for solving multi-objective meta-algorithms MOPSO and NSGA-II. Results: The results show that NSGA-II algorithm performs well. Conclusion: This research reduces the costs of production, distribution, inventory maintenance and fuel consumption. It can also help reduce product inventory and maintenance costs.
- Published
- 2020
7. Solving fuzzy robust facility layout problem equipped with cranes using MPS algorithm and modified NSGA-II
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Soroush Esmikhani, Hamed Kazemipoor, Farzad Movahedi Sobhani, and Seyyed Mohammad Hadji Molana
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Artificial Intelligence ,General Engineering ,Computer Science Applications - Published
- 2022
8. Designing sustainable closed-loop supply chain network with considering spot-to-point inflation and carbon emission policies: A case study
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Saeid Kalantari, Hamed Kazemipoor, Farzad Movahedi Sobhani, and Seyed Mohammad Hadji Molana
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General Computer Science ,General Engineering - Published
- 2022
9. A New Multi Objective Mathematical Model for Relief Distribution Location at Natural Disaster Response Phase
- Author
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Mahmood Reza Ganjipoor, Hamed Nozari, Morteza Khodabakhsh, Mohammad Ebrahim Sadeghi, and Hamed Kazemipoor
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General Economics (econ.GN) ,Multi-objective ,Flood myth ,Operations research ,Emergency management ,business.industry ,Computer science ,Supply chain ,Scale (chemistry) ,Locating-Distribution ,Response ,Phase (combat) ,FOS: Economics and business ,Reduction (complexity) ,Relief supplies ,Mathematical model ,Damages ,Natural disaster ,business ,Economics - General Economics - Abstract
Every year, natural disasters such as earthquake, flood, hurricane and etc. impose immense financial and humane losses on governments owing to their unpredictable character and arise of emergency situations and consequently the reduction of the abilities due to serious damages to infrastructures, increases demand for logistic services and supplies. First, in this study the necessity of paying attention to locating procedures in emergency situations is pointed out and an outline for the studied case of disaster relief supply chain was discussed and the problem was validated at small scale. On the other hand, to solve this kind of problems involving three objective functions and complicated time calculation, meta-heuristic methods which yield almost optimum solutions in less time are applied. The EC method and NSGA II algorithm are among the evolutionary multi-objective optimization algorithms applied in this case. In this study the aforementioned algorithm is used for solving problems at large scale.
- Published
- 2021
10. A Fuzzy Two-Echelon Model to Optimize Energy Consumption in an Urban Logistics Network with Electric Vehicles
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Azra Ghobadi, Mohammad Fallah, Reza Tavakkoli-Moghaddam, and Hamed Kazemipoor
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meta-heuristic algorithm ,Renewable Energy, Sustainability and the Environment ,heterogeneous fleet ,mixed-fleet vehicles ,Geography, Planning and Development ,two-echelon logistics network ,Building and Construction ,Management, Monitoring, Policy and Law ,electric vehicles - Abstract
With the increase in pollutants, the need to use electric vehicles (EVs) in various urban logistics activities is an increasingly important issue. Currently, there are issues with the efficiency of transport companies in recognizing the effects of uncertain factors in daily logistics operations. Thus, this research proposes a novel fuzzy two-echelon vehicle routing problem involving heterogeneous fleet EVs and internal combustion vehicles (ICVs). The first echelon is recyclable wastes collected from waste pickup points and transported to the primary centers by EVs. The second echelon is transporting recyclable wastes to recycling centers by ICVs. In the proposed models, fuzzy numbers are used to express the rate and energy consumption depending on the amount of load, vehicle speed, and recyclable waste. In addition, a penalty cost of the time windows is considered in both echelons. The models are solved by CPLEX and two meta-heuristic algorithms, gray wolf optimizer (GWO) and tabu search (TS), based on different instance sizes. The results show the efficiency of the proposed algorithms.
- Published
- 2022
11. Fuzzy decision analysis for project scope change management
- Author
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Farshad Shirazi, Reza Tavakkoli-Moghaddam, and Hamed Kazemipoor
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Engineering ,Process management ,lcsh:HF5691-5716 ,Process (engineering) ,0211 other engineering and technologies ,Strategy ,General Decision Sciences ,02 engineering and technology ,lcsh:Analysis ,Fuzzy logic ,Fuzzy Logic ,021105 building & construction ,0502 economics and business ,Project management triangle ,Fuzzy decision ,Hierarchy ,Project scope management ,Scope (project management) ,business.industry ,Management science ,Scope Control ,05 social sciences ,Change management ,lcsh:QA299.6-433 ,lcsh:Business mathematics. Commercial arithmetic. Including tables, etc ,business ,050203 business & management ,Decision analysis ,Scope change - Abstract
It is very important to manage and control projects with the consideration of the triple constraints; namely time, cost and scope. It is also extremely important to manage the scope and all the procurements needed to complete any project. During the project’s lifecycle many changes take place, either positively or negatively, which should be controlled. If the changes are not controlled we may have scope creep that has negative effect on the project. It is commonly considered a negative incident, and thus, should be kept away from the project. By considering this concept, in this paper, we discuss scope change and managing scope and fuzzy analytical hierarchy process is used in selecting the best strategy to manage scope change in projects.
- Published
- 2017
12. A green multi-objective integrated scheduling of production and distribution with heterogeneous fleet vehicle routing and time windows
- Author
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Seyyed Mohammad Hadji Molana, Maliheh Ganji, Seyed Mojtaba Sajadi, and Hamed Kazemipoor
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Supply chain management ,Operations research ,Renewable Energy, Sustainability and the Environment ,Computer science ,020209 energy ,Strategy and Management ,Tardiness ,Supply chain ,Ant colony optimization algorithms ,05 social sciences ,Scheduling (production processes) ,Particle swarm optimization ,02 engineering and technology ,Building and Construction ,Industrial and Manufacturing Engineering ,Vehicle routing problem ,050501 criminology ,0202 electrical engineering, electronic engineering, information engineering ,Programming paradigm ,0505 law ,General Environmental Science - Abstract
Scheduling the supply chain in an integrated manner is a quite fundamental subject in supply chain management. To consider due-dates with production and distribution times at the same time could lead to reduced costs and, thereby, increased profitability. Integrating the problems dealing with due-date assignment, production/distribution times, and routing, while incorporating environmental considerations, could not only increase the cohesion among different decision-making levels and reduce costs in the long run, it would also contribute to the improvement of environmental conditions and benefit the world population. In this study, the integrated supply chain scheduling problem features assignment of due dates, batch delivery, assignment to multiple heterogeneous vehicles based on their capacity, and delivery of customer orders in time-windows. The objective is to minimize distribution cost, fixed and variable fuel costs, the carbon emitted by the vehicles, total delivery tardiness, and customer dissatisfaction. In this model, the customers are categorized into five clusters based on the length of their association, how recently they began interacting, how often they interact, and the monetary value of their interaction with the organization. The members of these clusters are called core customers, potential customers, new customers, lost customers, and resource-consumption customers. A mixed integer non-linear programming model is introduced for this problem which is solved using three multi-objective metaheuristic algorithms: Multi-Objective Particle Swarm Optimization, Non-dominated Sorting Genetic Algorithm II, and Multi Objective Ant Colony Optimization. A number of performance criteria and statistical tests are used to evaluate the algorithms.
- Published
- 2020
13. A fuzzy inference- fuzzy analytic hierarchy process-based clinical decision support system for diagnosis of heart diseases
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Hamed Kazemipoor, Somayeh Nazari, Mohammad Fallah, and Amir Salehipour
- Subjects
0209 industrial biotechnology ,Fuzzy analytic hierarchy process ,Heart disease ,Process (engineering) ,Computer science ,Analytic hierarchy process ,02 engineering and technology ,Disease ,computer.software_genre ,Clinical decision support system ,020901 industrial engineering & automation ,Artificial Intelligence ,Health care ,0202 electrical engineering, electronic engineering, information engineering ,medicine ,Artificial Intelligence & Image Processing ,business.industry ,Management science ,General Engineering ,medicine.disease ,Expert system ,Computer Science Applications ,Risk analysis (engineering) ,020201 artificial intelligence & image processing ,business ,computer - Abstract
© 2017 Elsevier Ltd Many organizations and institutions are implementing accurate and practical tools to accelerate decision-making process. In this regard, hospitals and healthcare centers are not exceptions, in particular, because they directly impact the health and well-being of the community. When it comes to disease diagnosis, practitioners may have different opinions, which lead to different decisions and actions. On the other hand, the amount of available information, even in a case of a typical disease is so vast that rapid and accurate decision-making may be difficult. For example, practitioners may prescribe several expensive tests in order to diagnose a heart disease whereas many of those tests might not even be required. Accordingly, a Clinical Decision Support System (CDSS) can be very helpful here. In particular, such a CDSS can be developed as an expert system for those patients who have a high likelihood of developing heart diseases. This study develops an expert system based on Fuzzy Analytic Hierarchy Process (AHP) and Fuzzy Inference System in order to evaluate the condition of patients who are being examined for heart diseases. The Fuzzy AHP is used to calculate weights for different criteria that impact developing heart diseases, and the Fuzzy Inference System is used to assess and evaluate the likelihood of developing heart diseases in a patient. The developed system has been implemented in a hospital in Tehran. The outcomes show efficiency and accuracy of the developed approach.
- Published
- 2018
14. Solving a novel multi-skilled project scheduling model by scatter search
- Author
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Reza Tavakkoli-Moghaddam, P. Shahnazari-Shahrezaei, and Hamed Kazemipoor
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Difficult problem ,Project network ,lcsh:T55.4-60.8 ,Computer science ,business.industry ,Information technology ,Schedule (project management) ,scatter search ,Industrial and Manufacturing Engineering ,Tabu search ,Project scheduling problem ,lcsh:Industrial engineering. Management engineering ,Artificial intelligence ,Arithmetic ,business ,Word (computer architecture) ,Project scheduling model - Abstract
A multi-skilled project scheduling problem (MSPSP) has generally been presented to schedule information technology projects in deterministic conditions. The contribution of this model is to consider the resources, called 'staff members'. These members are regarded as valuable, renewable, and discrete resources with different multiple skills. The different skills of staff members, as well as the project network's activity requirement of different skills, cause this problem to become a special type of multi-mode resource-constrained project scheduling problem (MM-RCPSP), with a huge number of modes. Taking into account the importance of this issue and the few studies performed on this problem, a novel mathematical model for the MSPSP is presented. Since the complexity of this problem is NP-hard, an efficient scatter search (SS) algorithm is developed to solve such a difficult problem. This proposed SS is capable of generating optimised solutions in small sizes, and the excellent solutions in large sizes are compared with the solutions reported by a proposed Tabu search (TS) algorithm. 'n Veeldoel projekskeduleringsvraagstuk (MSPSP) word voorgehou vir skedulering onder deterministiese toestande van inligtingstegnologieprojekte. Die model word aangewend vir hulpbronne genaamd "personeellede". Die bronne is waardevol, hernubaar, diskreet en beskik oor uiteenlopende vaardighede. Die eienskappe van die vraagstuk berus by uiteenlopendheid. Vir die voorafgaande omstandighede word 'n nuwe model geskep vir die hantering van eienaardighede. Aangesien die problem NP-moeilik is, word 'n doeltreffende spreisoek-algoritme gebruik met groot sukses.
- Published
- 2013
15. Solving a multi-objective multi-skilled manpower scheduling model by a fuzzy goal programming approach
- Author
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Reza Tavakkoli-Moghaddam, Parisa Shahnazari-Shahrezaei, and Hamed Kazemipoor
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Engineering ,Service (systems architecture) ,Operations research ,business.industry ,Management science ,Applied Mathematics ,Scheduling (production processes) ,Vagueness ,Fuzzy logic ,law.invention ,Satisfaction level ,law ,Modelling and Simulation ,Modeling and Simulation ,CLARITY ,Production (economics) ,Fuzzy goal programming ,business - Abstract
Manpower scheduling is an intricate problem in production and service environments with the purpose of generating fair schedules that consider employers’ objectives and employees’ preferences as much as possible. However, sometimes, vagueness of information related to employers’ objectives and employees’ preferences leads to the fuzzy nature of the problem. This paper presents a multi-objective manpower scheduling model regarding the lack of clarity on the target values of employers’ objectives and employees’ preferences. Hence, a fuzzy goal programming model is developed for the presented model. Afterwards, two fuzzy solution approaches are used to convert the fuzzy goal programming model to two single-objective models. Finally, the results obtained by both single-objective models are compared with each other to select the solution that has the greatest degree of the satisfaction level of employers’ objectives and employees’ preferences.
- Published
- 2013
16. Solving a new fuzzy multi-objective model for a multi-skilled manpower scheduling problem by particle swarm optimization and elite tabu search
- Author
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Reza Tavakkoli-Moghaddam, Parisa Shahnazari-Shahrezaei, and Hamed Kazemipoor
- Subjects
Engineering ,Mathematical optimization ,Job shop scheduling ,business.industry ,Mechanical Engineering ,Particle swarm optimization ,Fuzzy logic ,Industrial and Manufacturing Engineering ,Tabu search ,Computer Science Applications ,Scheduling (computing) ,Control and Systems Engineering ,Multi objective model ,business ,Fuzzy goal programming ,Software - Abstract
Manpower scheduling is a complicated problem to solve that strives to satisfy employers’ objectives and employees’ preferences as much as possible by generating fairly desirable schedules. But sometimes, objectives and preferences may not be determined precisely. This problem causes manpower scheduling takes the fuzzy nature. This paper presents a new fuzzy multi-objective mathematical model for a multi-skilled manpower scheduling problem considering imprecise target values of employers’ objectives and employees’ preferences. Hence, a fuzzy goal programming model is developed for the presented mathematical model and two fuzzy solution approaches are used to convert the fuzzy goal programming model to two single-objective models. Since the complexity of a manpower scheduling problem is NP-hard, the single-objective models are solved by two meta-heuristics, namely particle swarm optimization and elite tabu search. Eventually, the performance of the proposed algorithms is verified and the results are compared with each other to select the best schedules.
- Published
- 2012
17. Solving a mixed-integer linear programming model for a multi-skilled project scheduling problem by simulated annealing
- Author
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Reza Tavakkoli-Moghaddam, Hamed Kazemipoor, and Parisa Shahnazari-Shahrezaei
- Subjects
Project network ,Mathematical optimization ,Heuristic (computer science) ,Computer science ,lcsh:HF5735-5746 ,Scheduling (production processes) ,Schedule (project management) ,lcsh:Business records management ,Solver ,General Business, Management and Accounting ,Simulated annealing ,Mixed integer linear programming ,Nurse scheduling problem ,Project scheduling ,Integer programming ,Metaheuristic - Abstract
Article history: Received July 20, 2011 Received in Revised form October, 12, 2011 Accepted 15 October 2011 Available online 20 October 2011 A multi-skilled project scheduling problem (MSPSP) has been generally presented to schedule a project with staff members as resources. Each activity in project network requires different skills and also staff members have different skills, too. This causes the MSPSP becomes a special type of a multi-mode resource-constrained project scheduling problem (MM-RCPSP) with a huge number of modes. Given the importance of this issue, in this paper, a mixed integer linear programming for the MSPSP is presented. Due to the complexity of the problem, a metaheuristic algorithm is proposed in order to find near optimal solutions. To validate performance of the algorithm, results are compared against exact solutions solved by the LINGO solver. The results are promising and show that optimal or near-optimal solutions are derived for small instances and good solutions for larger instances in reasonable time. © 2012 Growing Science Ltd. All rights reserved.
- Published
- 2012
18. A differential evolution algorithm to solve multi-skilled project portfolio scheduling problems
- Author
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Parisa Shahnazari-Shahrezaei, Reza Tavakkoli-Moghaddam, Amir Azaron, and Hamed Kazemipoor
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Mathematical optimization ,Job shop scheduling ,Operations research ,Mechanical Engineering ,Schedule (project management) ,Industrial and Manufacturing Engineering ,Tabu search ,Computer Science Applications ,Scheduling (computing) ,Control and Systems Engineering ,Differential evolution ,Goal programming ,Project portfolio management ,Metaheuristic ,Software ,Mathematics - Abstract
A multiskilled project portfolio scheduling problem (MSPPSP) is an extension of a multiobjective multimode resource-constrained project portfolio scheduling problem that is generally propounded to schedule a set of projects performed by human skills in an organization. The main idea of the MSPPSP is to consider resources that are called staff members to perform projects’ activities in different required skills. Since the required staff members have various skills, different combinations of skills are applied to accomplish the project. These definitions cause to encounter a huge number of modes while performing activities of a project. In this paper, a novel goal programming model for the multiobjective MSPPSP with precedence constraints that aim at finding a minimum deviation from the expected time to complete each project and assignment of resources is presented. To solve such a hard problem, an efficient metaheuristic algorithm based on differential evolution (DE) is developed. To evaluate the efficiency of the proposed DE algorithm, the results are compared to the results of the tabu search algorithm and the optimal results. The comparison confirms the effectiveness of the DE algorithm. Finally, regarding the size of organizations in terms of staff members, the maximum number of the determined structure projects, which is performable with minimum delay from aspiration times, is examined.
- Published
- 2012
19. Locating workstations in tandem automated guided vehicle systems
- Author
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Amir Salehipour, Hamed Kazemipoor, and Leila Moslemi Naeini
- Subjects
Waiting time ,Engineering ,Tandem ,Workstation ,business.industry ,Total flow ,Heuristic (computer science) ,Mechanical Engineering ,Real-time computing ,Automated guided vehicle ,Industrial and Manufacturing Engineering ,Computer Science Applications ,law.invention ,Industrial Engineering & Automation ,Control and Systems Engineering ,law ,Cumulative flow diagram ,Focus (optics) ,business ,Software ,Simulation - Abstract
This paper presents a new solution framework to locate the workstations in the tandem automated guided vehicle (AGV) systems. So far, the research has focused on minimizing the total flow or minimizing the total AGV transitions in each zone. In this paper, we focus on minimizing total cumulative flow among workstations. This objective allocates workstations to an AGV route such that total waiting time of workstations to be supplied by the AGV is minimized. We develop a property which simplifies the available mathematical formulation of the problem. We also develop a heuristic algorithm for the problem. Computational results show that our heuristic could yield very high-quality solutions and in many cases optimal solutions. © 2010 Springer-Verlag London Limited.
- Published
- 2010
20. The new ranking method of the decision making units in DEA: with an approach to modifying the cross efficiency method
- Author
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Nasser Shahsavari Pour, Hamed Kazemipoor, Esmaeil Najafi, and Behzad Paryzad
- Subjects
Flexibility (engineering) ,Cross efficiency ,Ranking ,Computer science ,Delicacy ,Control and Systems Engineering ,Data envelopment analysis ,Data mining ,computer.software_genre ,computer ,Industrial and Manufacturing Engineering - Abstract
There is no doubt that organisations need an operation evaluation and measurement for having more efficiency and an optimal usage of their limited sources. One of the most practical methods for evaluating the operation is using the data envelopment analysis. Hence, data envelopment analysis (DEA) and ranking decision making units (DMU) are the most favourite subjects for the researchers. This method has modified on a different style on this article that has removed the existence of multiple optimal answers in the CCR (Chames-Cooper and Rhodes). In other words, the acquired ranks of the units are particular and have achieved with a special delicacy. In order to show the efficiencies of the method, some examples have presented that had achieved the more desirable and accurate ranking. The calculated results of performing this method have compared with the Anderson-Peterson method and its flexibility has studied according to the analysis of variance (ANOVA).
- Published
- 2018
21. Partitioning machines in tandem AGV systems based on 'balanced flow strategy' by simulated annealing
- Author
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Reza Tavakkoli-Moghaddam, Amir Salehipour, Mir-Bahador Aryanezhad, and Hamed Kazemipoor
- Subjects
Computer. Automation ,Engineering ,Workstation ,business.industry ,Mechanical Engineering ,Cellular manufacturing ,Automated guided vehicle ,Industrial and Manufacturing Engineering ,Computer Science Applications ,law.invention ,Software ,Flow (mathematics) ,Control and Systems Engineering ,law ,Simulated annealing ,Balanced flow ,business ,Engineering sciences. Technology ,Algorithm ,Simulation ,Integer (computer science) - Abstract
A tandem automated guided vehicle (AGV) system deals with grouping workstations into some non-overlapping areas and assigning to each area exactly one AGV. This paper presents a new non-linear integer mathematical model to group n machines into N loops to minimize both inter-loop and intra-loop flow simultaneously based on balanced-loops strategy and inter-machine flows taken from ideas of cellular manufacturing systems. Due to computational difficulties of exact methods in solving the proposed model, a simulated annealing (SA) algorithm is proposed. A number of test problems are generated at random and solved by the proposed SA in order to show the efficiency of the algorithm. Finally, the results are reported by both the Lingo software and the proposed SA algorithm.
- Published
- 2007
22. SOLVING A BI-OBJECTIVE MANPOWER SCHEDULING PROBLEM CONSIDERING THE UTILITY OF OBJECTIVE FUNCTIONS
- Author
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R Tavakkoli Moghaddam, Hamed Kazemipoor, and P Shahnazari Shahrezaei
- Subjects
Workforce scheduling ,Mathematical optimization ,ComputingMilieux_THECOMPUTINGPROFESSION ,Job shop scheduling ,Computer science ,General Engineering ,Scheduling (production processes) ,Bi objective ,Dynamic priority scheduling ,Deadline-monotonic scheduling - Abstract
This paper presents a novel bi-objective manpower scheduling problem that minimizes the penalty incurred by the employees' assignment at lower skill levels than their real skills and maximizes the employees' utility by assigning them at desired skill levels in some shifts/days. Employees are classified in two specialist groups and three skill levels in each specialization. In addition, the presented model executes some essential work regulations. This paper also proposes a solution procedure based on the utility of objective values. Applying this procedure, an effective point is obtained for the given problem. This is the point where both objective functions have the highest utility simultaneously.
- Published
- 2011
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