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A Multi-Objective Anti-Predatory NIA for E-Commerce Logistics Optimization Problem

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  • Rohit Kumar Sachan

    (Motilal Nehru National Institute of Technology, India)

  • Dharmender Singh Kushwaha

    (Motilal Nehru National Institute of Technology, India)

Abstract

Nature-inspired algorithms (NIAs) have established their promising performance to solve both single-objective optimization problems (SOOPs) and multi-objective optimization problems (MOOPs). Anti-predatory NIA (APNIA) is one of the recently introduced single-objective algorithm based on the self-defense behavior of frogs. This paper extends APNIA as multi-objective algorithm and presents the first proposal of APNIA to solve MOOPs. The proposed algorithm is a posteriori version of APNIA, which is named as multi-objective anti-predatory NIA (MO-APNIA). It uses the concept of Pareto dominance to determine the non-dominated solutions. The performance of the MO-APNIA is established through the experimental evaluation and statistically verified using the Friedman rank test and Holm-Sidak test. MO-APNIA is also employed to solve a multi-objective variant of hub location problem (HLP) from the perspective of the e-commerce logistics. Results indicate that the MO-APNIA is also capable to finds the non-dominated solutions of HLP. This finds immense use in logistics industry.

Suggested Citation

  • Rohit Kumar Sachan & Dharmender Singh Kushwaha, 2021. "A Multi-Objective Anti-Predatory NIA for E-Commerce Logistics Optimization Problem," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 12(4), pages 1-27, October.
    • Handle: RePEc:igg:jamc00:v:12:y:2021:i:4:p:1-27
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