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Efficiency of Heuristic Algorithms in Solving Waste Collection Vehicle Routing Problem: A Case Study

Author

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  • Nur Azriati Mat*

    (Institute of Strategic Industrial Decision Modelling, School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, Kedah, Malaysia)

  • Aida Mauziah Benjamin

    (Institute of Strategic Industrial Decision Modelling, School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, Kedah, Malaysia)

  • Syariza Abdul-Rahman

    (Institute of Strategic Industrial Decision Modelling, School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, Kedah, Malaysia)

Abstract

This paper investigated the efficiency of six heuristic algorithms from prior studies in the attempt to solve issues related to waste collection, namely: (i) Nearest Greedy (NG), (ii) Further from Depot (FFD), (iii) Different Initial Customer (DIC), (iv) Savings Approach, (v) Sweep Algorithm, and (vi) Different Initial Customer based on Sweep Algorithm. In fact, these heuristics have been employed to solve several routing problems in past studies, but the performance of each heuristic has never been compared. Hence, this paper looked into the efficiency of these heuristics by testing them on a real case study of waste collection problem in a district located at the north of Peninsular Malaysia. Several solutions obtained from these heuristics were compared with solutions implemented by the waste collection company, especially in terms of the total distance travelled. As a result, the computational results exhibited that DIC generated the best solutions, when compared to other heuristics, with a 12% reduction of the total travel distance.

Suggested Citation

  • Nur Azriati Mat* & Aida Mauziah Benjamin & Syariza Abdul-Rahman, 2018. "Efficiency of Heuristic Algorithms in Solving Waste Collection Vehicle Routing Problem: A Case Study," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 695-700:6.
    • Handle: RePEc:arp:tjssrr:2018:p:695-700
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    References listed on IDEAS

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