Invasive Weed Optimization Algorithm for Minimizing Total Weighted Earliness and Tardiness Penalties on a Single Machine under Aging Effect

摘要

In this paper, minimizing total weighted tardiness and earliness criteria on a single machine is considered. Job processing time is a linear function of its starting time and each job has a distinct due date. In this study an Invasive Weed Optimization (IWO) algorithm is proposed for machine scheduling problem. Because the local search operator in IWO algorithm is designed for continuous problem only, a simple and efficient coding and decoding technique is applied to map the discrete feasible space of the permutation to a number. Then, this number is used to produce the solution. The computational results show that the performance of the proposed algorithm is much better than the GA algorithm for this problem in finding the best solutions.