A Novel Metaheuristics To Solve Mixed Shop Scheduling Problems

TL;DR

This paper introduces a new hybrid metaheuristic combining Bacterial Foraging Optimization and Ant Colony Optimization to effectively solve complex Mixed Shop Scheduling problems, outperforming existing methods.

Contribution

The paper proposes a novel hybrid metaheuristic approach specifically designed for Mixed Shop Scheduling problems, integrating two bio-inspired algorithms for improved performance.

Findings

The proposed algorithm effectively minimizes makespan in Mixed Shop Scheduling.

It outperforms existing algorithms in computational experiments.

The approach demonstrates robustness across various test instances.

Abstract

This paper represents the metaheuristics proposed for solving a class of Shop Scheduling problem. The Bacterial Foraging Optimization algorithm is featured with Ant Colony Optimization algorithm and proposed as a natural inspired computing approach to solve the Mixed Shop Scheduling problem. The Mixed Shop is the combination of Job Shop, Flow Shop and Open Shop scheduling problems. The sample instances for all mentioned Shop problems are used as test data and Mixed Shop survive its computational complexity to minimize the makespan. The computational results show that the proposed algorithm is gentler to solve and performs better than the existing algorithms.