scholarly journals Solving the Cubic Cell Formation Problem Using Simulated Annealing

2022 ◽  
Vol 12 (1) ◽  
pp. 0-0
Keyword(s):  
Simulated Annealing ◽  
Manufacturing Systems ◽  
Cell Formation ◽  
Cell Formation Problem ◽  
Major Objective ◽  
Minimum Value ◽  
Formation Problem ◽  
Neighbourhood Search ◽  
Problem Instances ◽  
Solution Methodology

The Cubic Cell Formation Problem (CCFP) in cellular manufacturing systems consists in decomposing a production system into a set of manufacturing cells, and assigning workers to cells besides parts and machines. The major objective is to obtain manageable cells. Manageable cells mean cells with a minimum value of inter-cell moves of parts and workers and a minimum value of heterogeneity within cells. In this paper, a solution methodology based on a modified simulated annealing heuristic with a proposed neighbourhood search procedure is proposed. The methodology allows building multiple configurations by giving to the decision-maker the ability to control some parameters. Experimental results show that the proposed algorithm gives a promising performance for all problem instances found in the literature.

Manufacturing cell formation with flexible processing capabilities and worker assignment: Comparison of constraint programming and integer programming approaches

2017 ◽  
Vol 232 (11) ◽  
pp. 2054-2068 ◽  
Author(s):  
Adil Baykasoğlu ◽  
Şeyda Topaloğlu ◽  
Filiz Şenyüzlüler
Keyword(s):  
Integer Programming ◽  
Constraint Programming ◽  
Manufacturing Systems ◽  
High Efficiency ◽  
Programming Model ◽  
Cell Formation ◽  
Programming Approach ◽  
Cell Formation Problem ◽  
Formation Problem ◽  
Complex Constraints

Cell formation deals with grouping of machines and parts in manufacturing systems according to their compatibility. Manufacturing processes are surrounded with an abundance of complex constraints which should be considered carefully and represented clearly for obtaining high efficiency and productivity. Constraint programming is a new approach to combinatorial optimization and provides a rich language to represent complex constraints easily. However, the cell formation problems are well suited to be solved by constraint programming approach since the problem has many constraints such as part-machine requirements, availabilities in the system in terms of capacity, machine and worker abilities. In this study, the cell formation problem is modeled using machine, part processing and worker flexibilities via resource element–based representation. Resource elements define the processing requirements of parts and processing capabilities of machines and workers, which are resource-independent capability units. A total of 12 case problems are generated, and different search phases of constraint programming are defined for the solution procedure. The cell formation problem is modeled in both constraint programming and integer programming, and a comparative analysis of constraint programming and integer programming model solutions is done. The results indicate that both the models are effective and efficient in the solution of the cell formation problem.

APPLYING SIMULATED ANNEALING TO A GENERALIZED CELL FORMATION PROBLEM CONSIDERING ALTERNATIVE ROUTINGS AND MACHINE RELIABILITY

2014 ◽  
Vol 31 (04) ◽  
pp. 1450021 ◽  
Author(s):  
JAVID JOUZDANI ◽  
FARNAZ BARZINPOUR ◽  
MOHAMMAD ALI SHAFIA ◽  
MOHAMMAD FATHIAN
Keyword(s):  
Simulated Annealing ◽  
Manufacturing System ◽  
Simulated Annealing Algorithm ◽  
Cellular Manufacturing ◽  
Cell Formation ◽  
Cell Formation Problem ◽  
Cellular Manufacturing System ◽  
Exact Methods ◽  
Setup Cost ◽  
Formation Problem

One of the most important steps in designing a cellular manufacturing system is cell formation which includes grouping the machines in cells and the parts as part families, so that the costs are minimized. Several aspects of the problem should be taken into account in cell formation; more specifically, machines and their reliability are among the most important issues that should be modelled correctly. Another important facet of a cellular manufacturing system is material handling cost consisting of inter-cellular and intra-cellular movement costs. In addition, setup cost may play a significant role in decision-making in many real world problems of cell formation. Obviously, cell formation cannot be completed without considering the demands for parts. Considering all these aspects of the problem in this research, a generalized model for solving cell formation problem is proposed. Exact methods, e.g., B&B, are cumbersome in solving such complex models for large-size problems. Therefore, in this paper, a modified version of simulated annealing algorithm is designed and numerical examples are provided to show that the proposed method is efficient and effective.

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