(ACO+GPE) for solving the traveling salesman Problem (TSP)

dc.contributor.authorSOUADIA, KHAOULA ICHRAK
dc.contributor.authorDJABOU, BOUTHEINA
dc.date.accessioned2022-03-22T08:32:22Z
dc.date.available2022-03-22T08:32:22Z
dc.date.issued2021
dc.description.abstractToday, optimization methods inspired from nature are widely used to solve optimization problems, due to their ability to provide innovative solutions for complex problems and it becomes more effective especially if we use hybrid methods. Therefore, we proposed a new model (ACO+GPE) to solve the traveling salesman problem. We applied the model to real problems, then we compared the results with the results of another model (ACO+PSO+3-OPT). KEY WORDS: Ant colony optimization, general pairwise exchange, hybrid methods, the traveling salesman problem Résumé Aujourd'hui, les méthodes d’inspiration biologique sont largement utilisées pour résoudre des problèmes d’optimisation, en raison de leur capacité à apporter des solutions innovantes à des problèmes complexes et elle devient plus efficace surtout si l'on utilise des méthodes hybrides. Par conséquent, nous avons proposé un nouveau modèle (ACO+GPE) pour résoudre le problème du voyageur de commerce. Nous avons appliqué le modèle sur des problèmes réels, puis on a comparé les résultats avec les résultats d'un autre modèle (ACO+PSO+3-OPT). Mots-clés : optimisation par colonies de fourmis, GPE, des méthodes hybrides, le problème du voyageur de commerce الملخص اليوم ، تُستخدم طرق التحسين المستوحاة من الطبيعة على نطاق واسع لحل مشكالت التحسين ، نظ ًرا لقدرتها على تقديم ا هجينة. لذلك ، اقترحنا نموذ ًجا جديدا لحل حلول مبتكرة للمشكالت المعقدة وتصبح أكثر فاعلية خاصة إذا استخدمنا طرقً مشكلة البائع المتجول. قمنا بتطبيق النموذج على مشاكل حقيقية ، ثم قمنا بمقارنة النتائج بنتائج نموذج آخر. للكلمات المفتاحية طرق حساب مشتقة من الطبيعة طرق هجينة مشكلة البائع المتجولen_US
dc.identifier.issnMM/573
dc.identifier.urihttp://10.10.1.6:4000/handle/123456789/2166
dc.language.isoenen_US
dc.publisherUniversité de Bordj Bou Arreridj Faculty of Mathematics and Computer Scienceen_US
dc.subjectAnt colony optimization, general pairwise exchange, hybrid methods, the traveling salesman problemen_US
dc.subject: optimisation par colonies de fourmis, GPE, des méthodes hybrides, le problème du voyageur de commerceen_US
dc.subjectللكلمات المفتاحية طرق حساب مشتقة من الطبيعة طرق هجينة مشكلة البائع المتجولen_US
dc.title(ACO+GPE) for solving the traveling salesman Problem (TSP)en_US
dc.typeThesisen_US

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In this work, we are interested in studying the traveling salesman problem by proposing a hybrid method for solving the TSP , this method combines two algorithms, ant colony optimization and general pairwise exchange (ACO+GPE), then comparing the results with another existing method which combining three algorithms ant colony optimization, particle swarm optimization and 3-OPT algorithm (ACO+PSO+3-OPT). We have mentioned combinatorial optimization problems and among this problems the well-known traveling salesman which ranges among NP-hard problems We discuss Ant Colony Optimization (ACO), which belongs to the group of evolutionary techniques and presents the approach used in the application of ACO to the TSP. We also discuss the general pairwise exchange (GPE) We investigated the capabilities of the hybrid method for solving optimization problems better than improvement methods alone Finally, we applied the algorithm on five distance matrix (EIL51, BERLIN52, ST70, EIL76, RAT99, and KROA200) and compare the results with the results of the other model, finding that the other model gives better results but the proposing model takes shorter time. We will end this thesis with the following perspectives: • We suggest adding the particle swarm optimization PSO to this proposing model and see if (ACO+GPE+PSO) model is good for solving the traveling salesman problem or not. • You have to learn how to program earlier.

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