Aspiration level-based multi-objective quasi oppositional Jaya algorithm to solve multi-objective solid travelling salesman problem with carbon emission

Aaishwarya Bajaj and Jayesh M. Dhodiya

International Journal of Operational Research, 2025, vol. 54, issue 3, 372-392

Abstract: The multi-objective solid travelling salesman problem (MOSTSP) is a complex optimisation problem as it employs multiple conveyances while travelling. In this paper, a newly developed aspiration level-based multi-objective quasi oppositional Jaya (AL-based MOQO Jaya) algorithm is used to tackle MOSTSP addressed within a crisp environment. A real-life example of Surat City is considered for 10 and 50 nodes, with five distinct objectives: cost, time, risk, distance, and carbon emission, with carbon-constrained. The obtained outcomes are compared with the results of the hybrid genetic algorithm (HGA) and the CPLEX optimisation tool. Remarkably, the AL-based MOQO Jaya algorithm exhibits significantly low computational time as compared to CPLEX and HGA. Furthermore, the performance of the algorithm is the study using coverage. The paper, concludes that the AL-based MOQO Jaya algorithm efficiently solves the MOSTSP, with effective output and provides alternative decision-making solutions to decision-makers.

Keywords: multi-objective solid travelling salesman problem; MOSTSP; aspiration level; carbon emission; multi-objective quasi oppositional Jaya; CPLEX. (search for similar items in EconPapers)
Date: 2025
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