Ant colony-based algorithms for scheduling parallel batch processors with incompatible job families
type: Item
instance of: scholarly article
title: Ant colony-based algorithms for scheduling parallel batch processors with incompatible job families
zbMATH Open document ID: 1184.90065
DOI: 10.1504/IJMOR.2010.029691
author: M. Venkataramana
author: N. R. Srinivasa Raghavan
published in: International Journal of Mathematics in Operational Research
publication date: 2010-04-15T00:00:00Z
review text: Summary: 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.
Mathematics Subject Classification ID: 90B35
Mathematics Subject Classification ID: 90C59
zbMATH DE Number: 5693414
zbMATH Keywords: batch processors
zbMATH Keywords: scheduling
zbMATH Keywords: TWT
zbMATH Keywords: total weighted tardiness
zbMATH Keywords: heuristics
zbMATH Keywords: ACO
zbMATH Keywords: ant colony optimisation
zbMATH Keywords: batch processing
MaRDI profile type: Publication
full work available at URL: ijmor.2010.029691
OpenAlex ID: W2035094564
description: scientific article; zbMATH DE number 5693414