جستجوی مقالات مرتبط با کلیدواژه « tabu search » در نشریات گروه « صنایع »

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.

Multi-manned assembly line balancing problems (MALBPs) can be usually found in plants producing large-sized high-volume products such as automobiles and trucks. In this paper, a cost-oriented version of MALBPs, namely, CMALBP, is addressed. This class of problems may arise in final assembly lines of products in which the manufacturing process is very labor-intensive. Since CMALBP is NP-Hard, a heuristic approach based on a tabu search algorithm is developed to solve the problem. The proposed algorithm uses two neighborhood generation mechanisms, namely swap and mutation, that effectively collaborate with each other to build new feasible solutions; moreover, two separate tabu lists (associated with the two generation mechanisms) are used to check if moving to a new generated neighbor solution is forbidden or allowed. To examine the efficiency of the proposed algorithm, some experimental instances are collected from the literature and solved. The obtained results show the effectiveness of the proposed tabu search approach.

Automated Guided Vehicle System (AGVS) provides the flexibility and automation demanded by Flexible Manufacturing System (FMS). However, with the growing concern on responsible management of resource use, it is crucial to manage these vehicles in an efficient way in order reduces travel time and controls conflicts and congestions. This paper presents the development process of a new Memetic Algorithm (MA) for optimizing partitioning problem of tandem AGVS. MAs employ a Genetic Algorithm (GA), as a global search, and apply a local search to bring the solutions to a local optimum point. A new Tabu Search (TS) has been developed and combined with a GA to refine the newly generated individuals by GA. The aim of the proposed algorithm is to minimize the maximum workload of the system. After all, the performance of the proposed algorithm is evaluated using Matlab. This study also compared the objective function of the proposed MA with GA. The results showed that the TS, as a local search, significantly improves the objective function of the GA for different system sizes with large and small numbers of zone by 1.26 in average.

The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems. The algorithm provides a better performance on large-scaled instances and gained advantage in terms of CPU time. In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.

A cutting stock problem is one of the main and classical problems in operations research that is modeled as Lp < /div> problem. Because of its NP-hard nature, finding an optimal solution in reasonable time is extremely difficult and at least non-economical. In this paper, two meta-heuristic algorithms, namely simulated annealing (SA) and tabu search (TS), are proposed and developed for this type of the complex and large-sized problem. To evaluate the efficiency of these proposed approaches, several problems are solved using SA and TS, and then the related results are compared. The results show that the proposed SA gives good results in terms of objective function values rather than TS.

A tandem AGV configuration connects all cells of a manufacturing area by means of non-overlapping, sin-gle-vehicle closed loops. Each loop has at least one additional P/D station, provided as an interface between adjacent loops. This study describes the development of three tabu search algorithms for the design of tandem AGV systems. The first algorithm was developed based on the basic definition of a tandem network. The sec-ond and third algorithms, consider no preset number of loops and try to evenly distribute workload among loops by using workload balance as their objective functions. They generate different design scenarios for the tandem network, which can be evaluated and selected using a multi-attribute objective function. The first al-gorithm and the partitioning algorithm presented by Bozer and Srinivasan are compared for randomly gener-ated problems. Results show that for large-scale problems, the partitioning algorithm often leads to infeasible configurations with crossed loops in spite of its shorter running time. However, the newly developed algo-rithm avoids infeasible configurations and often yields better objective function values.