Material handling considerations in the FMS loading problem with full routing flexibility

Abstract

This study exploits machining and routing flexibility to effectively deal with the material handling requirements resulting from a frequently changing demand mix in a manufacturing system where material handling is a bottleneck. For this purpose, the objective function of the operation and tool loading problem is selected as the minimisation of the total distance traveled by parts during their production. Versatile machines and the flexible process plans offer full routing flexibility that enable the same workpiece to be processed using alternative sequences of operations on alternative machines. Three mathematical programming (MP) models and a genetic algorithm (GA) are proposed to solve this problem. The proposed MP formulations include a mixed-integer nonlinear programming (MINLP) model and two mixed-integer programming (MIP) models, which offer different representations for the flexible process plans. The GA is integrated with linear programming for fitness evaluation and incorporates several adaptive strategies for diversification. The performances of these solution methods are tested through extensive numerical experiments. The MP models are evaluated on the basis of the exact solutions they yield as well as how they lend themselves for GA fitness evaluation. The GA–LP integration works successfully for this hard-to-solve problem.