A new approach for workshop design

被引:9
作者
Yalaoui, Naim [1 ,2 ]
Mahdi, Halim [2 ]
Amodeo, Lionel [1 ]
Yalaoui, Farouk [1 ]
机构
[1] Univ Technol Troyes, FRE CNRS 2848, Inst Charles Delaunay OSI, Troyes, France
[2] Caillau Co, F-92130 Issy Les Moulineaux, France
关键词
Group technology; Genetic algorithm; Ant colony optimization; Guided local search; Facility layout problem; Quadratic assignment problem; CELLULAR MANUFACTURING SYSTEMS; FACILITY LAYOUT PROBLEM; GENETIC ALGORITHM; GROUP TECHNOLOGY; SIMILARITY COEFFICIENT; MACHINE; OPTIMIZATION; CELLS; FAMILIES; ROUTES;
D O I
10.1007/s10845-009-0368-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we solve a combined group technology problem with a facility layout problem (FLP). This new approach is called T-FLP. We have developed a hybrid algorithm containing three main steps. The first one, called MPGV (Machine Part Grouping with Volume) is a decomposition method that can create families of product and machine groups based on a volume data matrix. The second one consists on assigning machines to fixed locations, using as a constraint, the solution of the MPGV. This problem is solved as a Quadratic Assignment Problem (QAP). In the third step, we make a global evaluation of all the solutions. A loop on cells is performed using a minimum and maximum number of cells. This loop can choose the appropriate number of cells based on the best solution of a global evaluation. The hybrid algorithm is implemented with two different rules for taking into account the constraint of the MPGV solution. This has generated two methods called YMAY1 and YMAY2. In the MPGV we use a data oriented genetic algorithm. The QAP is solved with an Ant Colony Optimization mixed with a Guided Local Search (ACOGLS). This method has been used to solve a real industrial case. For estimating the efficiency of our method, we have compared our results with an optimal solution obtained by complete enumeration (an exact method).
引用
收藏
页码:933 / 951
页数:19
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