SEGMENT RANDOM INSERTION PERTURBATION SCHEME (SRIPS) GENETIC ALGORITHM FOR MANUFACTURING INDUSTRY

Abstract

This paper lays down a formal framework for simultaneous scheduling of machines- automated guided vehicles (AGVs) and tools in a multi-machine flexible manufacturing system (FMS) while accounting for transport times of parts to minimise makespan. To minimize tooling costs- a central tool magazine (CTM) is suggested so that the tools are ‘shared’. AGVs and tool transporter (TT) carry jobs and tools between machines. The complexity of including sequencing of job operations on machines- assignment of AGVs and tools to job operations and corresponding trip operations such as the empty trip and loaded trip times of AGVs and a CTM in scheduling is greater. The scope of this paper is to propose a nonlinear Mixed Integer Programming (MIP) model to minimize makespan. Since the problem is known to be NP hard- it is conjectured and then verified that the intelligent behaviour of chromosomes and genes can be effectively used to lay down a metaheuristic algorithm known as a segment random insertion perturbation scheme genetic algorithm (SRIPSGA) suitable for the problem at hand- and the results have been tabulated and analyzed.