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

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.