alireza alinezhad; Abolfazl kazemi; Marzieh Karimi
Abstract
Location, routing and allocation decisions in supply chain management philosophy is undoubtedly one of the most important issues have very effect on the supply chain cost reduction and customer satisfaction. This paper presents an integrated approach to the distribution network. The objective functions ...
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Location, routing and allocation decisions in supply chain management philosophy is undoubtedly one of the most important issues have very effect on the supply chain cost reduction and customer satisfaction. This paper presents an integrated approach to the distribution network. The objective functions of the proposed mathematical model consist of minimizing the total costs associated with transportation and warehouse rental costs and also minimize the risk of the system. The model has high computational complexity and the exact method of solving it is not possible in a reasonable time. To solve the proposed model a multi-objective meta-heuristic algorithm which, known as the objective harmony search algorithm is presented. To demonstrate the effectiveness and efficiency of the proposed algorithm in solving the model, algorithm parameters are adjusted in the best possible rates using the Taguchi method. Then a random sample of the issues generated and the performance of the proposed algorithm comparing with NSGA-ǁ and NRGA are evaluated
Abstract
One of the most important problems of logistic networks is designing and analyzing of the distribution network. The design of distribution systems raises hard combinatorial optimization problems. In recent years, two main problems in the design of distribution networks that are location of distribution ...
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One of the most important problems of logistic networks is designing and analyzing of the distribution network. The design of distribution systems raises hard combinatorial optimization problems. In recent years, two main problems in the design of distribution networks that are location of distribution centres and routing of distributors are considered together and created the location-routing problem. The location-routing problem (LRP), integrates the two kinds of decisions. The classical LRP, consists in opening a subset of depots, assigning customers to them and determining vehicle routes, to minimize total cost of the problem. In this paper, a dynamic capacitated location-routing problem is considered that there are a number of potential depot locations and customers with specific demand and locations, and some vehicles with a certain capacity. Decisions concerning facility locations are permitted to be made only in the first time period of the planning horizon but, the routing decisions may be changed in each time period. In this study, customer demands depend on the products offering prices. The corresponding model and presented results related to the implementation of the model by different solution methods have been analysed by different methods. A hybrid heuristic algorithm based on particle swarm optimization is proposed to solve the problem. To evaluate the performance of the proposed algorithm, the proposed algorithm results are compared with exact algorithm optimal value and lower bounds. The comparison between hybrid proposed algorithm and exact solutions are performed and computational experiments show the effectiveness of the proposed algorithm.
Behnam Vahdani
Abstract
Today, intense competition in global markets has forced companies to design and manage of supply chains in a better way. Since the role of three factors: location, routing and inventory is important to continue the life of a supply chain so, integration of these three elements will create an efficient ...
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Today, intense competition in global markets has forced companies to design and manage of supply chains in a better way. Since the role of three factors: location, routing and inventory is important to continue the life of a supply chain so, integration of these three elements will create an efficient and effective supply chain. In this study, we investigate the problem of supply chain network design that including routing and inventory problem consist of flow allocation, vehicle routing between facilities, locating distribution centers and also consider the maximum coverage for respond to customer demand. Proposed mathematical model is a nonlinear mixed integer programming model for location-routing-inventory problem in the four-echelon supply chain by considering the multiple conflicting goals of total cost, travel time and maximum coverage. In order to solve the proposed model, three meta-heuristic algorithms (MOPSO, MSGA_II and NRGA) has been used. The accuracy of mathematical model and proposed algorithms are evaluated through numerical examples
Seyed Mohammad Taghi Fatemi Ghomi; Ehsan Arabzadeh; Behrooz Karimi
Abstract
Home health care services have a key importance in modern societies. Most organizations working in this area in Iran use the traditional procedure to plan and manage medical staff and determine the arrangement of visiting patients. This procedure often increases costs and reduces the satisfaction of ...
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Home health care services have a key importance in modern societies. Most organizations working in this area in Iran use the traditional procedure to plan and manage medical staff and determine the arrangement of visiting patients. This procedure often increases costs and reduces the satisfaction of patients. In this paper, a multi-period routing and scheduling model is proposed in order to visit patients and provide them medical services. Considering both dependency and independence of a patient's visits with each other, assuming the model as multi-depot as well as multi period are some innovations of this study. The main purpose of the proposed model is to reduce total costs of home health care organization. Model has been solved in small scale by GAMS software. To solve the model in large scale, developed Variable neighborhood search is proposed and compared with simulated annealing algorithm and ant colony system. Results show that costs are decreased and the proposed algorithm has better performance
