A novel 0-1 linear integer programming model and NSGA-II for dynamic machine tool selection and operation allocation problem in FMS

Majid Soolaki

International Journal of Industrial and Systems Engineering, 2013, vol. 14, issue 4, 463-483

Abstract: Flexible manufacturing systems (FMS) consist of some multi functional machines that are linked together through material-handling system and the whole of the system control by a central computer. One of the most important problems in production planning of FMS is machine tool selection and operation allocation problem that directly influences the production costs and times. Here, a novel 0-1 linear integer programming model is presented in such a way that each part and each tool can move during the production phase. The objective of this model is to determine a machine-tool combination for each operation of the part type. The objective function calculates some production costs, such as machining costs, setup costs, material-handling costs, tool movement costs and maximum transformation times. This paper uses an elitist multi-objective evolutionary algorithm based on the non-dominated sorting genetic algorithm-II (NSGA-II), for solving the dynamic machine tool selection and operation allocation problem in FMS. Experimental results indicate effectiveness of the proposed algorithm for solving the problem.

Keywords: flexible manufacturing systems; FMS; machine-tool combination; operation allocation; part movement; tool movement; transformation times; multi-objective optimisation; non-dominated sorting genetic algorithm-II; NSGA-II; genetic algorithms; production planning; machine tool selection; linear integer programming; production costs. (search for similar items in EconPapers)
Date: 2013
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