A thorough study of the performance of simulated annealing in the traveling salesman problem under correlated and long tailed spatial scenarios

Silva, Roberto da; Filho, Eliseu Venites; Alves, Alexandre

doi:10.1016/j.physa.2021.126067

Cited by 8 publications

(1 citation statement)

References 14 publications

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“…Johannes J. Schneider et al [13] propose a new simplified approach to derive adaptive cooling schedule based on retained data in memory. Another interesting work is the paper of Roberto da Silva et al [14] that studies the effects of the statistics on the coordinates of the points when they apply a standard simulated annealing algorithm to the traveling salesman problem.…”

Section: Related Workmentioning

confidence: 99%

A new improved simulated annealing for traveling salesman problem

Adil,

Lakhbab

2023

Math. Model. Comput.

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Simulated annealing algorithm is one of the most popular metaheuristics that has been successfully applied to many optimization problems. The main advantage of SA is its ability to escape from local optima by allowing hill-climbing moves and exploring new solutions at the beginning of the search process. One of its drawbacks is its slow convergence, requiring high computational time with a good set of parameter values to find a reasonable solution. In this work, a new improved SA is proposed to solve the well-known travelling salesman problem. In order to improve SA performance, a population-based improvement procedure is incorporated after the acceptance phase of SA, allowing the algorithm to take advantage of the social behavior of some solutions from the search space. Numerical results were carried out using known TSP instances from TSPLIB and preliminary results show that the proposed algorithm outperforms in terms of solution quality, the other comparison algorithms.

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Section: Related Workmentioning

confidence: 99%

A new improved simulated annealing for traveling salesman problem

Adil,

Lakhbab

2023

Math. Model. Comput.

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Solving a new application of asymmetric TSP by modified migrating birds optimization algorithm

Tibet

Duman

2023

Evol. Intel.

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Turkish Cashier Problem with time windows and its solution by matheuristic algorithms

Bassaleh,

Duman

2024

RAIRO-Oper. Res.

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Turkish Cashier Problem (TCP) is a new application area of the traveling salesman problem that was introduced to the literature recently. In this problem, the cashier can use public transportation or take a taxi where the cashier must visit multiple customer locations while minimizing the total transportation cost. In this study, we introduce a more realistic version of this problem where time has been integrated. This aspect is achieved by imposing time intervals within which the cashier must visit the customers. We name this problem as the TCP with time windows (TCPwTW). We develop several matheuristic algorithms to solve the TCPwTW: a modified version of the Simplify and Conquer (SAC) algorithm that was suggested for the TCP, simulated annealing (SA), original and modified versions of the migrating birds optimization (MBO) algorithm coupled with mathematical programming. We also tried to find the exact optimum using a Solver where for complex problems, only lower bounds were found. Numerical experimentation reveals that while for problems with loose time intervals, an exact solver can be considered. Once the time intervals tighten up, the best solutions can be obtained using matheuristics involving SA and MBO.

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A thorough study of the performance of simulated annealing in the traveling salesman problem under correlated and long tailed spatial scenarios

Cited by 8 publications

References 14 publications

A new improved simulated annealing for traveling salesman problem

A new improved simulated annealing for traveling salesman problem

Solving a new application of asymmetric TSP by modified migrating birds optimization algorithm

Turkish Cashier Problem with time windows and its solution by matheuristic algorithms

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