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Preference Vector Ant Colony System for Minimising Make-span and Energy Consumption in a Hybrid Flow Shop

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Multi-objective Evolutionary Optimisation for Product Design and Manufacturing

Abstract

Traditionally, scheduling problems usually deal with the objectives related to production efficiency (e.g., the make-span, the total completion time, the maximum lateness and the number of tardy jobs). However, sustainable manufacturing should minimise the energy consumption during production process. Energy consumption not only constitutes a major portion of total production cost but also results in significant environmental effects. In this chapter, we discuss a multi-objective scheduling problem in a hybrid flow shop. Two objectives considered in the proposed model are to minimise make-span and energy consumption. These two objectives are often in conflict with each other. A Preference Vector Ant Colony System (PVACS) is developed to search for a set of Pareto-optimal solutions using meta-heuristics for multi-objective optimisation. PVACS allows the search in the solution space to focus on the specific areas which are of particular interest to decision-makers, instead of searching for the entire Pareto frontier. This is achieved by maintaining a separate pheromone matrix for each objective, respectively and assigning each ant a preference vector that represents the preference between the two objectives of the decision-makers. The performance of PVACS was compared to two well-known multi-objective genetic algorithms: SPEA2 and NSGA-II. The experimental results show that PVACS outperforms the other two algorithms.

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Acknowledgments

The authors would like to thank Xiaolin Li, Qi Tan, Song Zhang for technical assistance. This work was supported by National Natural Science Foundation of China (70821001), Research Fund for the Doctoral Program of Higher Education of China (200803580024), HKSAR ITF (GHP/042/07LP), HKSAR RGC GRF (HKU 712508E), and HKU Research Committee grants.

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Authors and Affiliations

  1. School of Management, University of Science and Technology of China, Hefei, China

    Bing Du

  2. School of Computer Science and Technology, University of Science and Technology of China, Hefei, China

    Huaping Chen

  3. Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, China

    George Q. Huang

  4. School of Automation, South China University of Technology, Guangzhou, China

    H. D. Yang

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  1. Bing Du
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  2. Huaping Chen
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  4. H. D. Yang
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Correspondence to Bing Du .

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Editors and Affiliations

  1. , Virtual Systems Research Centre, University of Skövde, Skövde, 541 28, Sweden

    Lihui Wang

  2. , Virtual Systems Research Centre, University of Skövde, Skövde, 541 28, Sweden

    Amos H. C. Ng

  3. , Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, 208016, Uttar Pradesh, India

    Kalyanmoy Deb

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Du, B., Chen, H., Huang, G.Q., Yang, H.D. (2011). Preference Vector Ant Colony System for Minimising Make-span and Energy Consumption in a Hybrid Flow Shop. In: Wang, L., Ng, A., Deb, K. (eds) Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. Springer, London. https://doi.org/10.1007/978-0-85729-652-8_9

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  • DOI: https://doi.org/10.1007/978-0-85729-652-8_9

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