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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Journal of Optimization in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Genetic Algorithm,Supply chain network design,Tabu Search,harmony search,Multi-mode demand
- چکیده:
- چکیده انگلیسی: The supply chain network design not only assists organizations production process (e.g.,plan, control and execute a product’s flow) but also ensure what is the growing need for companies in a longterm. This paper develops a three-echelon supply chain network problem including multiple plants, multiple distributors, and multiple retailers with amulti-mode demand satisfaction policy inside of production planning and maintenance. The problem is formulated as a mixed-integer linear programming model. Because of its NP-hardness, three meta-heuristic algorithms(i.e., tabu search, harmony search and genetic algorithm) are used to solve the given problem. Also, theTaguchi method is used to choose the best levels of the parameters of the proposedmeta-heuristic algorithms. The results show that HS has abetter solution quality than two other algorithms.
- انتشار مقاله: 02-02-1398
- نویسندگان: Amir Fatehi Kivi,Esmaeil Mehdizadeh,Reza Tavakkoli-Moghaddam,Seyed Esmaeil Najafi
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Optimization in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: reliability,Supply Chain,Aggregate production planning,NSGA-II,Multi-objective,harmony search
- چکیده:
- چکیده انگلیسی: In this research, a bi-objective model is developed to deal with a supply chain including multiple suppliers, multiple manufacturers, and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem. This bi-objective model aims to minimize the total cost of supply chain including inventory costs, manufacturing costs, work force costs, hiring, and firing costs, and maximize the minimum of suppliers' and producers' reliability by the considering probabilistic lead times, to improve the performance of the system and achieve a more reliable production plan. To solve the model in small sizes, a ε-constraint method is used. A numerical example utilizing the real data from a paper and wood industry is designed and the model performance is assessed. With regard to the fact that the proposed bi-objective model is NP-Hard, for large-scale problems one multi-objective harmony search algorithm is used and its results are compared with the NSGA-II algorithm. The results demonstrate the capability and efficiency of the proposed algorithm in finding Pareto solutions.
- انتشار مقاله: 28-10-1396
- نویسندگان: Mohammad Ramyar,Esmaeil Mehdizadeh,Seyyed Mohammad Hadji Molana
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Optimization in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Theory of Constraints,Outsourcing,Branch and Bound Algorithm,Product-mix
- چکیده:
- چکیده انگلیسی: One of the most important decision making problems in many production systems is identification and determination of products and their quantities according to available resources. This problem is called product-mix. However, in the real-world situations, for existing constrained resources, many companies try to provide some products from external resources to achieve more profits. In this paper, an integrated product-mix-outsourcing problem (IPMO) is considered to answer how many products should be produced inside of the system or purchased from external resources. For this purpose, an algorithm based on Theory of Constraints (TOC) and Branch and Bound (B&B) algorithm is proposed. For investigation of the proposed algorithm, a numerical example is presented. The obtained results show the optimal result by the new algorithm is as same as the results of integer linear programming.
- انتشار مقاله: 18-07-1395
- نویسندگان: Esmaeil Mehdizadeh,Saeed Jalili
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Industrial and Systems Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Finite planning horizon,Flow shop,Determining lot sizes,Hybrid particle swarm optimization,Basic period
- چکیده:
- چکیده انگلیسی: Many authors have examined lot sizing, scheduling and sequence of multi-product flow shops, but most of them have assumed that set up times are independent of sequence. Whereas dependence of set up times to sequence is more common in practice. Hence, in this paper, we examine the discussed problem with hypothesis of dependence of set up times to sequence and cyclic schedule policy in basic period form. To do so, a mixed integer non-linear programming (NLP) model is developed for this problem. To solve the model these techniques are applied: Heuristic G-group for determining the frequency of item production and assigning product to periods and three meta heuristic methods including hybrid Particle swarm optimization , hybrid Vibration damping optimization hybrid genetic algorithm are used to determine the sequence and economic lot sizes of each item. In addition, to compare these methods, some random problems are produced and computation of them shows the substantial superiority of hybrid Particle swarm optimization.
- انتشار مقاله: 15-12-1388
- نویسندگان: Mohammad Aliabadi,Fariborz Jolai,Esmaeil Mehdizadeh,Masoud Jenabi
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Engineering, Transactions A: Basics
- نوع مقاله: Journal Article
- کلمات کلیدی: Genetic Algorithm,Supply chain network design,Preventive maintenance,Tabu Search,harmony search,Production-distribution
- چکیده:
- چکیده انگلیسی: The supply chain network design (SCND) implicates decision-making at a strategic level and makes it possible to create an effective and helpful context for managing. The aim of the network is to minimize the total cost so that customer's demands should be met. Preventive maintenance is pre-determined work performed to a schedule with the aim of preventing the wear and tear or sudden failure of equipment components. Unfortunately, there is very little work on the issues of preventive maintenance in the SCND. At first, a mixed integer nonlinear programming model (MINLP) is formulated that maximaize the profit of the network. Since the SCND is an NP-hard problem, we use three meta-heuristic algorithms, namely tabu search, harmony search and genetic algorithm to solve the given problem. Taguchi method is also used to adjust the significant parameters of the forgoing meta-heuristics and select the optimal levels of the influential factors for the better algorithm performance. The results of different numerical experiments endorse the effectiveness of the HS algorithm.
- انتشار مقاله: 03-12-1397
- نویسندگان: Amir Fatehi-Kivi,Esmaeil Mehdizadeh,Reza Tavakkoli-Moghaddam
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Engineering, Transactions A: Basics
- نوع مقاله: Journal Article
- کلمات کلیدی: Simulated Annealing,Lot,Sizing,Safety stocks,Vibration damping optimization,harmony search
- چکیده:
- چکیده انگلیسی: This paper proposes a mixed integer programming model for single-item capacitated lot-sizing problem with setup times, safety stock, demand shortages, outsourcing and inventory capacity. Due to the complexity of problem, three meta-heuristics algorithms named simulated annealing (SA), vibration damping optimization (VDO) and harmony search (HS) have been used to solve this model. Additionally, Taguchi method is conducted to calibrate the parameters of the meta-heuristics and select the optimal levels of the algorithm’s performance influential factors. Computational results on a set of randomly generated instances show the efficiency of the HS against VDO and SA.
- انتشار مقاله: 11-10-1348
- نویسندگان: Esmaeil Mehdizadeh,Amir Fatehi Kivi
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Engineering, Transactions A: Basics
- نوع مقاله: Journal Article
- کلمات کلیدی: Simulated Annealing,Lot,Sizing,Safety stocks,Vibration damping optimization,harmony search
- چکیده:
- چکیده انگلیسی: This paper proposes a mixed integer programming model for single-item capacitated lot-sizing problem with setup times, safety stock, demand shortages, outsourcing and inventory capacity. Due to the complexity of problem, three meta-heuristics algorithms named simulated annealing (SA), vibration damping optimization (VDO) and harmony search (HS) have been used to solve this model. Additionally, Taguchi method is conducted to calibrate the parameters of the meta-heuristics and select the optimal levels of the algorithm’s performance influential factors. Computational results on a set of randomly generated instances show the efficiency of the HS against VDO and SA.
- انتشار مقاله: 11-10-1348
- نویسندگان: Esmaeil Mehdizadeh,Amir Fatehi Kivi
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Genetic Algorithm,Mathematical Modeling,Production Scheduling,Flexible Job-Shop,Reverse Flows,Taguchi Method
- چکیده:
- چکیده انگلیسی: One of the important issues in the field of flexible job-shop production scheduling is reverse flows within a single production unit, as is the case in the assembly/disassembly plants. This paper studies the flexible job-shop scheduling by employing reverse flows approach, which consists of two flows of jobs at each stage in opposite directions. The problem can be used only if you have two flows: the first one going from first stage to last stage, and the second flow going from last stage to first stage. Then, a mathematical model of problem is provided to minimize the maximal completion time of the jobs (i.e., the makespan). Because of the complexity solving and proving that this problem ranked on NP-hard problems, we proposed meta-heuristic algorithm genetic (GA). Also, The parameters of these algorithm GA and their appropriate operators are obtained by the use of the Taguchi experimental design. The computational results validate outperforms proposed algorithm GA.
- انتشار مقاله: 28-01-1396
- نویسندگان: Fatemeh Soleimaninia,Esmaeil Mehdizadeh
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Fuzzy Goal Programming,Genetic Algorithm,Multi-Objective Programming,Aggregate production planning,Tabu search algorithm
- چکیده:
- چکیده انگلیسی: In this paper a non linear integrated fuzzy multi-objective production planning model with the labor learning and machines deterioration effects is presented. The objective function consists of two quantitative objectives namely increase profits and reduces the cost of system failure and a qualitative objective namely increases the satisfaction rate of the customers. Different weights for objectives and modification of the objectives by using fuzzy goal programming method are considered to convert the fuzzy multi-objective model to a deterministic single-objective model and the obtained model is solved by Genetic algorithm and Tabu search algorithm. Finally, the solution obtained from two algorithms compared together by using hypothesis test of equality of means. Experimental results show the proposed Genetic algorithm for solving the model has higher performance than the Tabu search algorithm.
- انتشار مقاله: 22-07-1394
- نویسندگان: Esmaeil Mehdizadeh,Rasa Ghazizadeh
- مشاهده