Local search methods for job shop scheduling problem

Abstract

Rapid globalization over the past few years is leading to intense competition among manufacturers throughout the world over lower product costs, shorter product life cycles and more product variety. An effective scheduling system for the various jobs is needed to cope with this competition in order to reduce inventory levels and cycle times while improving on-time delivery and the utilization of critical resources. Combinatorial Optimization Problems (COPs) is an important research area due to its common occurrence in real-world scheduling problems in many industries. A representative problem of COPs is the Job Shop Scheduling Problem (JSSP). This project investigates various approximate methods including the constructive approach of Insertion algorithms and Local Search techniques of Variable Neighbourhood Search and Simulated Annealing incorporated with Multiple-Type Individual Enhancement. It discusses an improvement for makespan calculation.