X Chen, Y Zhou, Z Tang, Q Luo - Applied Soft Computing, 2017 - Elsevier
Abstract The Travelling Salesman Problem (TSP) is one of the most well-known combinatorial optimization problems and has attracted a lot of interests from researchers …
A Uğur, D Aydin - Advances in Engineering software, 2009 - Elsevier
Traveling salesman problem (TSP) is one of the extensively studied combinatorial optimization problems and tries to find the shortest route for salesperson which visits each …
We study the hybridization of the self-organizing map (SOM) in an evolutionary algorithm to solve the Euclidean traveling salesman problem (TSP). The evolutionary dynamics consist …
Z Xu, Y Wang, S Li, Y Liu, Y Todo… - IEEJ Transactions on …, 2016 - Wiley Online Library
This paper describes an artificial immune algorithm (IA) combined with estimation of distribution algorithm (EDA), named IA‐EDA, for the traveling salesman problem (TSP). Two …
H Wang, N Zhang, JC Créput - Neurocomputing, 2017 - Elsevier
This paper proposes a parallel computation model for the self-organizing map (SOM) neural network applied to Euclidean traveling salesman problems (TSP). This model is intended for …
We investigate a parallelized divide-and-conquer approach based on a self-organizing map (SOM) in order to solve the Euclidean traveling salesman problem (TSP). Our approach …
J Bajo, JF de Paz, Y de Paz, JM Corchado - Expert Systems with …, 2009 - Elsevier
This paper presents an intelligent environment developed for monitoring patients' health care in execution time in hospital environments. The CBPMP (case-based planner for …
S Gao, W Wang, H Dai, F Li, Z Tang - IEICE transactions on …, 2008 - search.ieice.org
Both the clonal selection algorithm (CSA) and the ant colony optimization (ACO) are inspired by natural phenomena and are effective tools for solving complex problems. CSA can exploit …
This paper presents a technique that uses the Wang recurrent neural network with the “Winner Takes All” principle to solve the traveling salesman problem (TSP). When the Wang …