Solving the Multi-objective Travelling Salesman Problem by an Amalgam of Fruit Fly Optimization and Ant Colony Optimization
Received: 26 March 2024 | Revised: 27 April 2024 and 17 May 2024 | Accepted: 19 May 2024 | Online: 5 July 2024
Corresponding author: Archana A. Deshpande
Abstract
In this article, the multi-objective Travelling Salesman Problem (TSP), which includes the optimization of two competing and incompatible goals, is taken into account. There is not a single ideal strategy that enhances all the objective functions at once. Usually, one of the goals is considered a constraint or both goals are combined into one objective function. This work provides an extremely efficient Ant Colony Optimization (ACO)-based multi-objective Fruit Fly Optimization Algorithm (FFOA). Using FFOA, which was normalized and initialized to the pheromone quantity for ACO, the present study first establishes a local solution. To evaluate the optimization results a combined method of FFOA and ACO is carried out.
Keywords:
multi-objective travelling salesman problem, fruit fly optimization, ant colony optimizationDownloads
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Copyright (c) 2024 Archana A. Deshpande, Seema Raut, Nalini V. Vaidya
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