Estimation-based metaheuristics for the probabilistic traveling salesman problem

Abstract

The probabilistic traveling salesman problem (PTSP) is a central problem in stochastic routing. Recently, we have shown that empirical estimation is a promising approach to devise highly effective local search algorithms for the PTSP. In this paper, we customize two metaheuristics, an iterated local search algorithm and a memetic algorithm, to solve the PTSP. This customization consists in adopting the estimation approach to evaluate the solution cost, exploiting a recently developed estimationbased local search algorithm, and tuning the metaheuristics parameters. We present an experimental study of the estimation-based metaheuristic algorithms on a number of instance classes. The results show that the proposed algorithms are highly effective and that they define a new state-of-the-art for the PTSP.

Putting Continuous Metaheuristics to Work in Binary Search Spaces

“…For genetic algorithms, it was used to work on economic dispatch problems [106]. Finally, local search [123] and memetic [123] metaheuristics were used to solve the traveling salesman problem.…”

“…The authors declare that they have no conflicts of interest. Probabilistic traveling salesman problem [123] by Grant CONICYT/FONDECYT/REGULAR/1160455, José García is supported by INF-PUCV 2016, and Gino Astorga is supported by Postgraduate Grant, Pontificia Universidad Católica de Valparaíso, 2015.…”

A Hybrid Particle Swarm Optimization – Simulated Annealing Algorithm for the Probabilistic Travelling Salesman Problem

“…Several other implementations of SA can be found in the literature. In [2], two estimation-based SA algorithms were developed using different acceptance criterion. In [16], the authors use the powerful global search capability of GA and the powerful partial search capability of SA, an improved SAGA is proposed in order to solve an specific problem in mining.…”

“…These three initial solution generators allow the GA to reduce computational time without decreasing the quality of the best reached solution. In [2,3], the authors present an Estimation-Based algorithm involving local search strategies. In both, the authors experiment with different metaheuristics applying an estimation-based customization strategy, to evaluate the solution cost of different PTSP instances, obtaining excellent results.…”

Integration of Visualization Techniques to Algorithms of Optimization of the Metaheuristics Ant Colony

“…To solve the problem we proposed: design a model of integration of visualization techniques to the ACO optimization algorithms, which would allow the user to guide the search of the solutions through their interaction with the visualization of the algorithm in real time and in this way improve their quality; and implement a software tool according to the model to solve TSP problems with the algorithm System of Ant Colony and user interaction [3].…”