Optimization of Dynamic Practical Job Shop Scheduling in Manufacturing

Abstract

Abstract: Scheduling concerned with searching for optimal (or near optimal) solution subject to a number of constraints. It is a problem of machines allocation over time to jobs completion. In real-world application, scheduling parameters are not always precise due to a variety of unexpected disruption such as machine breakdown, operator illness, unavailability of tool etc. Thus, deterministic scheduling approaches which rely on precise data are not suitable to cater this environment. Fuzzy logic allows the modelling of imprecise scheduling knowledge with linguistic variables defined by membership function showing the degree of preciseness of the data and the reasoning about the imprecise data using fuzzy rules. In this paper, we consider a dynamic job shop scheduling problem of finding an optimal policy to process n jobs on m machines even if machine(s) breakdown occurs. Fuzzy Tabu search approach for a real world job shop problem will be applied to find a feasible solution which minimized the makespan.