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Parallel processor scheduling for minimizing total weighted tardiness using ant colony optimization

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Abstract

In the modern business environment, meeting due dates and avoiding delay penalties are very important goals that can be accomplished by minimizing total weighted tardiness. We consider a scheduling problem in a system of parallel processors with the objective of minimizing total weighted tardiness. Our aim in the present work is to develop an efficient algorithm for solving the parallel processor problem as compared to the available heuristics in the literature and we propose the ant colony optimization approach for this problem. An extensive experimentation is conducted to evaluate the performance of the ACO approach on different problem sizes with the varied tardiness factors. Our experimentation shows that the proposed ant colony optimization algorithm is giving promising results compared to the best of the available heuristics.

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Authors and Affiliations

  1. GM R&D and Strategic Planning, India Science Lab, Bangalore, 560066, India

    N. R. Srinivasa Raghavan

  2. Decision Sciences Laboratory, Department of Management Studies, Indian Institute of Science, Bangalore, 560012, India

    M. Venkataramana

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  1. N. R. Srinivasa Raghavan
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  2. M. Venkataramana
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Correspondence to N. R. Srinivasa Raghavan.

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Raghavan, N.R.S., Venkataramana, M. Parallel processor scheduling for minimizing total weighted tardiness using ant colony optimization. Int J Adv Manuf Technol 41, 986–996 (2009). https://doi.org/10.1007/s00170-008-1544-z

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  • DOI: https://doi.org/10.1007/s00170-008-1544-z

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