Mohammadreza Dabiri; Mehdi Yazdani; bahman naderi; Hasan Haleh
Abstract
In the real world, firms with hybrid flow-shop manufacturing environment generally facethe human resource constraint, salary cost increasment and efforts to make better use oflabor, in addition to machine constraint. Given the limitations of these resources, productdelivery requierements to customers ...
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In the real world, firms with hybrid flow-shop manufacturing environment generally facethe human resource constraint, salary cost increasment and efforts to make better use oflabor, in addition to machine constraint. Given the limitations of these resources, productdelivery requierements to customers have made the job rejection essential in order to meetdistinct customer requirements. Therefore, this research has studied the dual resourceconstrained hybrid flow-shop scheduling problem with job rejection in order to minimizethe total net cost (the sum of the total rejection cost and the total tardiness cost of jobs)which is widely used in many industries. In this article, a mixed integer linear programmingmodel has developed for the research problem. In addition, an improved sooty ternoptimization algorithm (ISTOA) has proposed to solve the large-sized problems as well asa decoding method due to the NP-hardness of the problem. In order to evaluate theproposed optimization algorithm, five well-known algorithms in the literature including(immunoglobulin-based artificial immune system (IAIS), genetic algorithm (GA), discreteartificial bee colony (DABC), improved fruit fly optimization (IFFO), effective modifiedmigrating birds optimization (EMBO)) have adapted with the proposed problem. Finally,the performance of the proposed optimization algorithm has investigated against theadapted algorithms. Results and evaluations show the good performance of the improvedsooty tern optimization algorithm.
Mehdi Yazdani
Abstract
This paper deals with the problem of two-stage assembly flow shop scheduling with considering sequence-independent setup times .The objective is to minimize totalcompletion times of all orders. In this problem, there are several orders for one type of product. Each ordered product is formed of several ...
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This paper deals with the problem of two-stage assembly flow shop scheduling with considering sequence-independent setup times .The objective is to minimize totalcompletion times of all orders. In this problem, there are several orders for one type of product. Each ordered product is formed of several different parts. At first, the parts are manufactured in a flow shop stage with some different machines and then they are assembled into a final product on a single machine. This paper presents three meta-heuristic algorithms, namely Parallel Variable Neighborhood Search (PVN) Artificial Immune Algorithm (AIA) and Simulated Annealing (SA), for solving under studied problem. The Taguchi experimental design method as an optimization technique is employed to tune different parameters and operators of presented algorithms. Also, Numerical experiments are used to evaluate the performance of the proposed algorithms. The results show that the PVNS algorithm performs better than the other algorithms
Ali Mohtashami; Amir Hossein Niknamfar
Abstract
Hazardous materials which are materials due to their chemical and physical properties impose significant risk to the safety of people and the environment. It's more complex routing transport of such material than normal materials. The Combination of the two subjects as the problem of locating and routing, ...
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Hazardous materials which are materials due to their chemical and physical properties impose significant risk to the safety of people and the environment. It's more complex routing transport of such material than normal materials. The Combination of the two subjects as the problem of locating and routing, it has created unified system to locating- routing problems. These problems determined optimal number and location of facilities at the same time and also set the optimal number of vehicles and their routes. The purpose of this study was design a network for the transportation of hazardous materials and includes supply levels, distribution (hub) and customers. Hence, it presented a mathematical model in order to minimizing costs and risk simultaneously. Hazardous materials sent from supplier to the hubs and deliveries to customers from there via routing by road transportation. It should be mentioned that in proposal model the hubs been locating In order to validate the model, prepared code GAMS In software and for the exact solution, sample problems with various dimensions were produced in the form of smart and random. For this purpose, was written an algorithm design in Matlab software. According to the problem was NP-Hard, presented a hybrid algorithm based on simulated annealing and genetic algorithms to solve large-scale. At the end of research the proposed algorithm were compared with the results of exact solution.
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
Mahnaz Afrasiyabi; Ahmad Sadeghi
Abstract
Models presented in inventory management, encompass varied parameters. Primary factor in classic models related to determination of the economical ordering quantity (EOQ) and the economical production quantity (EPQ), is to consider parameters like the setup cost, the holding cost and the demand rate, ...
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Models presented in inventory management, encompass varied parameters. Primary factor in classic models related to determination of the economical ordering quantity (EOQ) and the economical production quantity (EPQ), is to consider parameters like the setup cost, the holding cost and the demand rate, to be fixed. This characteristic leads to a great difference among the quantity of the economical ordering obtained in classic models and real-word conditions. For instance, It should be stated that not only the holding costs of spoiled and useless products are not always fixed, but also, they would be increased by passing time. This article is an attempt to develop classical EOQ and EPQ models by considering holding and purchasing cost as an increasing continuous function of the ordering cycle time. Due to the complexity of the considered problem, two meta-heuristic algorithms, including Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-objective Particle Swarm Optimization (MOPSO) are developed. Optimizing service level is considered as one of main apprehension in management science, that’s why increasing service level optimization would be evaluated as the second objective. As the performance of meta-heuristic algorithms is significantly influenced by calibrating their parameters, Taguchi methodology has been used to tune the parameters of the developed algorithms
Darush Mohamadi Zanjirani; Majid Esmailian; Saeedeh Jokar
Abstract
Process planning involves determining the most suitable and efficient manufacturing (assembly) processes and their sequence in order to produce a product (part). These processes should be compatible with required attributes in product design documentation. Process planning and scheduling optimization ...
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Process planning involves determining the most suitable and efficient manufacturing (assembly) processes and their sequence in order to produce a product (part). These processes should be compatible with required attributes in product design documentation. Process planning and scheduling optimization is done with Considering qualitative parameters which are affective on job shop and flexible system. Fuzzy Inference System and Meta-heuristic algorithms with multiple objective and goal functions are used to solving problem. Objective functions include minimization of cost and time of processing parts and maximizing the utility of the process design. based on the illustrated numerical example simulated annealing algorithm has better efficiency than imperialist competitive algorithm, particle swarm, bee colony.
Omid Amirtaheri; Mostafa Zandieh; Behrouz Dorri
Abstract
In this paper, we investigate a decentralized manufacturer-distributer supply chain. In addition to global advertisement, the manufacturer participates in the local advertising expenditures of distributer. Bi-level programming approach is applied to model the relationship between the manufacturer and ...
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In this paper, we investigate a decentralized manufacturer-distributer supply chain. In addition to global advertisement, the manufacturer participates in the local advertising expenditures of distributer. Bi-level programming approach is applied to model the relationship between the manufacturer and retailer under two power scenarios of stackelberg game framework and the optimal policies in pricing, advertising, inventory management and logistics are identified. Two hierarchical genetic algorithms are proposed to solve the bi-level programming models. Based on collected data from Iranian automotive spare parts aftermarket, several numerical experiments are carried out to evaluate the validity of proposed models as well as the efficiency and effectiveness of solution procedures.
