scholarly journals Improved Meta-Heuristic for Multi-Objective Integrated Procurement, Production and Distribution Problem of Supply Chain Network Under Fuzziness Uncertainties

2021 ◽  
Vol 17 (12) ◽  
pp. 1196-1209
Author(s):  
Kaoutar Douaioui ◽  
Mouhsene Fri ◽  
Charif Mabrouki ◽  
El Alami Semma
Author(s):  
Fariba Goodarzian ◽  
davood shishebori ◽  
Hadi Nasseri ◽  
Faridreza Dadvar

One of the main topics discussed in a supply chain is the production-distribution problem. Producing and distributing the products plays a key role in reducing the costs of the chain. To design a supply chain, a network of efficient management and production-distribution decisions is essential. Accordingly, providing an appropriate mathematical model for such problems can be helpful in designing and managing supply chain networks. Mathematical formulations must be drawn close to the real world due to the importance of supply chain networks. This makes those formulations more complicated. In this study, a novel multi-objective formulation is devised for the production-distribution problem of a supply chain that consists of several suppliers, manufacturers, distributors, and different customers. Also, a Mixed Integer Linear Programming (MILP) mathematical model is proposed for designing a multi-objective and multi-period supply chain network. In addition, grey flexible linear programming (GFLP) is done for a multi-objective production-distribution problem in a supply chain network. The network is designed for the first time to cope with the uncertain nature of costs, demands, and capacity parameters. In this regard, due to the NP-hardness and complexity of problems and the necessity of using meta-heuristic algorithms, NSGA-II and Fast PGA algorithm are applied and compared in terms of several criteria that emphasize the quality and diversity of the solutions.


Author(s):  
Fariba Goodarzian ◽  
Davood Shishebori ◽  
Hadi Nasseri ◽  
Faridreza Dadvar

One of the main topics discussed in a supply chain is the production-distribution problem. Producing and distributing the products plays a key role in reducing the costs of the chain. To design a supply chain, a network of efficient management and production-distribution decisions is essential. Accordingly, providing an appropriate mathematical model for such problems can be helpful in designing and managing supply chain networks. Mathematical formulations must be drawn close to the real world due to the importance of supply chain networks. This makes those formulations more complicated. In this study, a novel multi-objective formulation is devised for the production-distribution problem of a supply chain that consists of several suppliers, manufacturers, distributors, and different customers. Also, a Mixed Integer Linear Programming (MILP) mathematical model is proposed for designing a multi-objective and multi-period supply chain network. In addition, grey flexible linear programming (GFLP) is done for a multi-objective production-distribution problem in a supply chain network. The network is designed for the first time to cope with the uncertain nature of costs, demands, and capacity parameters. In this regard, due to the NP-hardness and complexity of problems and the necessity of using meta-heuristic algorithms, NSGA-II and Fast PGA algorithm are applied and compared in terms of several criteria that emphasize the quality and diversity of the solutions.


2021 ◽  
Author(s):  
Fatemeh Mohebalizadehgashti

Traditional logistics management has not focused on environmental concerns when designing and optimizing food supply chain networks. However, the protection of the environment is one of the main factors that should be considered based on environmental protection regulations of countries. In this thesis, environmental concerns with a mathematical model are investigated to design and configure a multi-period, multi-product, multi-echelon green meat supply chain network. A multi-objective mixed-integer linear programming formulation is developed to optimize three objectives simultaneously: minimization of the total cost, minimization of the total CO2 emissions released from transportation, and maximization of the total capacity utilization. To demonstrate the efficiency of the proposed optimization model, a green meat supply chain network for Southern Ontario, Canada is designed. A solution approach based on augmented εε-constraint method is developed for solving the proposed model. As a result, a set of Pareto-optimal solutions is obtained. Finally, the impacts of uncertainty on the proposed model are investigated using several decision trees. Optimization of a food supply chain, particularly a meat supply chain, based on multiple objectives under uncertainty using decision trees is a new approach in the literature. Keywords: Meat supply chain; Decision tree; Multi-objective programming; Mixed-integer linear programming; Augmented εε-constraint.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amir Rahimzadeh Dehaghani ◽  
Muhammad Nawaz ◽  
Rohullah Sultanie ◽  
Tawiah Kwatekwei Quartey-Papafio

PurposeThis research studies a location-allocation problem considering the m/m/m/k queue model in the blood supply chain network. This supply chain includes three levels of suppliers or donors, main blood centers (laboratories for separation, storage and distribution centers) and demand centers (hospitals and private clinics). Moreover, the proposed model is a multi-objective model including minimizing the total cost of the blood supply chain (the cost of unmet demand and inventory spoilage, the cost of transport between collection centers and the main centers of blood), minimizing the waiting time of donors in blood donating mobile centers, and minimizing the establishment of mobile centers in potential places.Design/methodology/approachSince the problem is multi-objective and NP-Hard, the heuristic algorithm NSGA-II is proposed for Pareto solutions and then the estimation of the parameters of the algorithm is described using the design of experiments. According to the review of the previous research, there are a few pieces of research in the blood supply chain in the field of design queue models and there were few works that tried to use these concepts for designing the blood supply chain networks. Also, in former research, the uncertainty in the number of donors, and also the importance of blood donors has not been considered.FindingsA novel mathematical model guided by the theory of linear programming has been proposed that can help health-care administrators in optimizing the blood supply chain networks.Originality/valueBy building upon solid literature and theory, the current study proposes a novel model for improving the supply chain of blood.


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