Amir Mollaei | Kharazmi University (original) (raw)

Papers by Amir Mollaei

Rairo-operations Research, 2019

Over the past few years, water allocation problem has increasingly spotlighted by governments, re... more Over the past few years, water allocation problem has increasingly spotlighted by governments, researchers and practitioners. As water plays an important role in people's life and business environment, the problem of water allocation should be considered carefully to properly satisfy demand of water consumers. In the real world applications, problems like water allocation are uncertain owing to long-term planning horizon of such problems. Therefore, employing efficient methods for tackling uncertainty of parameters should be regarded by field researchers. In this regard, this paper proposes a bi-objective mathematical programming model for water distribution network design. The extended model maximizes total profit of water distribution as well as maximizing priority of water transferring among water customer zones. Then, to cope effectively with uncertainty of parameters, a novel robust possibilistic programming method is applied. Then, fuzzy and robust fuzzy programming models are compared against each other and output results confirm superiority and effective performance of the robust fuzzy model in the water allocation problem. Also, output results of the extended model show its accurate performance that results in applicability of the model as a strong planning tool in real world cases.

international journal of management science and engineering management, Oct 23, 2018

One of the important issues in scheduling due to the frequent use of it in manufacturing industri... more One of the important issues in scheduling due to the frequent use of it in manufacturing industries and factories is the hybrid flow shop (HFS) scheduling problem. In this paper, a bi-objective mixed integer linear programming (MILP) model for the problem is presented in which blocking constraint is also considered. The first objective function tries to minimize the makespan and the second one tries to minimize the total costs of machine allocation at each stage. In fact, in this model, the number and the type of machines at each stage are determined by the model according to the processing and setup times and cost of machines. Because most issues in the real world are uncertain, in this study, processing times, sequence-dependent setup times, and costs are considered as uncertain parameters. The robust possibilistic programming (RPP) approach is used to cope with the uncertainty. In this paper, the realistic and the hard worst-case robust approaches are used. The realistic and the soft worst-case robust models became the same because we are only concerned about the robustness of the makespan. Comparing the results between fuzzy and robust fuzzy models shows that the realistic model is more suitable than fuzzy and hard worst-case models in terms of mean and standard deviation.

Over the past few years, water allocation problem has increasingly spotlighted by governments, re... more Over the past few years, water allocation problem has increasingly spotlighted by governments, researchers and practitioners. As water plays an important role in people’s life and business environment, the problem of water allocation should be considered carefully to properly satisfy demand of water consumers. In the real world applications, problems like water allocation are uncertain owing to long-term planning horizon of such problems. Therefore, employing efficient methods for tackling uncertainty of parameters should be regarded by field researchers. In this regard, this paper proposes a bi-objective mathematical programming model for water distribution network design. The extended model maximizes total profit of water distribution as well as maximizing priority of water transferring among water customer zones. Then, to cope effectively with uncertainty of parameters, a novel robust possibilistic programming method is applied. Then, fuzzy and robust fuzzy programming models are...

International Journal of Management Science and Engineering Management, Oct 23, 2019

ABSTRACT One of the important issues in scheduling due to the frequent use of it in manufacturing... more ABSTRACT One of the important issues in scheduling due to the frequent use of it in manufacturing industries and factories is the hybrid flow shop (HFS) scheduling problem. In this paper, a bi-objective mixed integer linear programming (MILP) model for the problem is presented in which blocking constraint is also considered. The first objective function tries to minimize the makespan and the second one tries to minimize the total costs of machine allocation at each stage. In fact, in this model, the number and the type of machines at each stage are determined by the model according to the processing and setup times and cost of machines. Because most issues in the real world are uncertain, in this study, processing times, sequence-dependent setup times, and costs are considered as uncertain parameters. The robust possibilistic programming (RPP) approach is used to cope with the uncertainty. In this paper, the realistic and the hard worst-case robust approaches are used. The realistic and the soft worst-case robust models became the same because we are only concerned about the robustness of the makespan. Comparing the results between fuzzy and robust fuzzy models shows that the realistic model is more suitable than fuzzy and hard worst-case models in terms of mean and standard deviation.

Rairo-operations Research, 2019

Over the past few years, water allocation problem has increasingly spotlighted by governments, re... more Over the past few years, water allocation problem has increasingly spotlighted by governments, researchers and practitioners. As water plays an important role in people's life and business environment, the problem of water allocation should be considered carefully to properly satisfy demand of water consumers. In the real world applications, problems like water allocation are uncertain owing to long-term planning horizon of such problems. Therefore, employing efficient methods for tackling uncertainty of parameters should be regarded by field researchers. In this regard, this paper proposes a bi-objective mathematical programming model for water distribution network design. The extended model maximizes total profit of water distribution as well as maximizing priority of water transferring among water customer zones. Then, to cope effectively with uncertainty of parameters, a novel robust possibilistic programming method is applied. Then, fuzzy and robust fuzzy programming models are compared against each other and output results confirm superiority and effective performance of the robust fuzzy model in the water allocation problem. Also, output results of the extended model show its accurate performance that results in applicability of the model as a strong planning tool in real world cases.

international journal of management science and engineering management, Oct 23, 2018

One of the important issues in scheduling due to the frequent use of it in manufacturing industri... more One of the important issues in scheduling due to the frequent use of it in manufacturing industries and factories is the hybrid flow shop (HFS) scheduling problem. In this paper, a bi-objective mixed integer linear programming (MILP) model for the problem is presented in which blocking constraint is also considered. The first objective function tries to minimize the makespan and the second one tries to minimize the total costs of machine allocation at each stage. In fact, in this model, the number and the type of machines at each stage are determined by the model according to the processing and setup times and cost of machines. Because most issues in the real world are uncertain, in this study, processing times, sequence-dependent setup times, and costs are considered as uncertain parameters. The robust possibilistic programming (RPP) approach is used to cope with the uncertainty. In this paper, the realistic and the hard worst-case robust approaches are used. The realistic and the soft worst-case robust models became the same because we are only concerned about the robustness of the makespan. Comparing the results between fuzzy and robust fuzzy models shows that the realistic model is more suitable than fuzzy and hard worst-case models in terms of mean and standard deviation.

Over the past few years, water allocation problem has increasingly spotlighted by governments, re... more Over the past few years, water allocation problem has increasingly spotlighted by governments, researchers and practitioners. As water plays an important role in people’s life and business environment, the problem of water allocation should be considered carefully to properly satisfy demand of water consumers. In the real world applications, problems like water allocation are uncertain owing to long-term planning horizon of such problems. Therefore, employing efficient methods for tackling uncertainty of parameters should be regarded by field researchers. In this regard, this paper proposes a bi-objective mathematical programming model for water distribution network design. The extended model maximizes total profit of water distribution as well as maximizing priority of water transferring among water customer zones. Then, to cope effectively with uncertainty of parameters, a novel robust possibilistic programming method is applied. Then, fuzzy and robust fuzzy programming models are...

International Journal of Management Science and Engineering Management, Oct 23, 2019

ABSTRACT One of the important issues in scheduling due to the frequent use of it in manufacturing... more ABSTRACT One of the important issues in scheduling due to the frequent use of it in manufacturing industries and factories is the hybrid flow shop (HFS) scheduling problem. In this paper, a bi-objective mixed integer linear programming (MILP) model for the problem is presented in which blocking constraint is also considered. The first objective function tries to minimize the makespan and the second one tries to minimize the total costs of machine allocation at each stage. In fact, in this model, the number and the type of machines at each stage are determined by the model according to the processing and setup times and cost of machines. Because most issues in the real world are uncertain, in this study, processing times, sequence-dependent setup times, and costs are considered as uncertain parameters. The robust possibilistic programming (RPP) approach is used to cope with the uncertainty. In this paper, the realistic and the hard worst-case robust approaches are used. The realistic and the soft worst-case robust models became the same because we are only concerned about the robustness of the makespan. Comparing the results between fuzzy and robust fuzzy models shows that the realistic model is more suitable than fuzzy and hard worst-case models in terms of mean and standard deviation.