The shifting bottleneck procedure for job shop scheduling
Management Science
A fast taboo search algorithm for the job shop problem
Management Science
Transportation Modeling: An Artificial Life Approach
ICTAI '02 Proceedings of the 14th IEEE International Conference on Tools with Artificial Intelligence
On Honey Bees and Dynamic Server Allocation in Internet Hosting Centers
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
An Advanced Tabu Search Algorithm for the Job Shop Problem
Journal of Scheduling
A bee colony optimization algorithm to job shop scheduling
Proceedings of the 38th conference on Winter simulation
A Bee Colony Optimization Algorithm for Traveling Salesman Problem
AMS '08 Proceedings of the 2008 Second Asia International Conference on Modelling & Simulation (AMS)
Expert Systems with Applications: An International Journal
Application of multi-objective bee colony optimization algorithm to automated red teaming
Winter Simulation Conference
Hi-index | 0.00 |
Scheduling is a crucial activity in semiconductor manufacturing industry. Effective scheduling in its operations leads to improvement in the efficiency and utilization of its equipment. Job Shop Scheduling is an NP-hard problem which is closely related to some of the scheduling activities in this industry. This paper presents an improved Bee Colony Optimization algorithm with Big Valley landscape exploitation as a biologically inspired approach to solve the Job Shop Scheduling problem. Experimental results comparing our proposed algorithm with Shifting Bottleneck Heuristic, Tabu Search Algorithm and Bee Colony Algorithm with Neighborhood Search on Taillard JSSP benchmark show that it is comparable to these approaches.