Title: Ant colony-based algorithms for scheduling parallel batch processors with incompatible job families
Authors: M. Venkataramana, N.R. Srinivasa Raghavan
Addresses: Decision Sciences Laboratory, Department of Management Studies, Indian Institute of Science, Bangalore 560 012, Karnataka, India. ' Customer Driven Advanced Vehicle Development Group, GM-India Science Lab, Bangalore 560 066, Karnataka, India
Abstract: In current dynamic business environments, meeting the customer due dates and avoiding delay penalties are very important. Our work concerns with the static scheduling of jobs to parallel identical batch processors for minimising the total weighted tardiness. It is assumed that the jobs are incompatible in respect of job families indicating that jobs from different families cannot be processed together. In practice, the problem cannot be solved using any classical OR algorithms in polynomial time due to the problem complexity. We develop metaheuristics, namely, the ant colony optimisation (ACO) approach to solve the problem efficiently. We propose three ant colony-based algorithms by using the structural properties of the problem. An extensive experimentation is conducted to evaluate the performance of the proposed algorithms on different problem sizes with the varied tardiness factors. Our experimentation shows that ACO-based algorithms perform better as compared to the available best dispatching rules and algorithms.
Keywords: batch processors; scheduling; TWT; total weighted tardiness; heuristics; ACO; ant colony optimisation; batch processing.
International Journal of Mathematics in Operational Research, 2010 Vol.2 No.1, pp.73 - 98
Available online: 01 Dec 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article