An efficient parallel genetic algorithm solution for vehicle routing problem in cloud implementation of the intelligent transportation systems
Mahdi Abbasi,Milad Rafiee,Mohammad Reza Khosravi,Mohammad Reza Khosravi,Alireza Jolfaei,Varun G. Menon,Javad Mokhtari Koushyar +6 more
TL;DR: A novel parallelization method of genetic algorithm (GA) solution of the Traveling Salesman Problem (TSP) is presented and the results confirm the efficiency of the proposed method for parallelizing GAs on many-core as well as on multi-core systems.
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Abstract: A novel parallelization method of genetic algorithm (GA) solution of the Traveling Salesman Problem (TSP) is presented. The proposed method can considerably accelerate the solution of the equivalent TSP of many complex vehicle routing problems (VRPs) in the cloud implementation of intelligent transportation systems. The solution provides routing information besides all the services required by the autonomous vehicles in vehicular clouds. GA is considered as an important class of evolutionary algorithms that can solve optimization problems in growing intelligent transport systems. But, to meet time criteria in time-constrained problems of intelligent transportation systems like routing and controlling the autonomous vehicles, a highly parallelizable GA is needed. The proposed method parallelizes the GA by designing three concurrent kernels, each of which running some dependent effective operators of GA. It can be straightforwardly adapted to run on many-core and multi-core processors. To best use the valuable resources of such processors in parallel execution of the GA, threads that run any of the triple kernels are synchronized by a low-cost switching mechanism. The proposed method was experimented for parallelizing a GA-based solution of TSP over multi-core and many-core systems. The results confirm the efficiency of the proposed method for parallelizing GAs on many-core as well as on multi-core systems.
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Citations
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A concise guide to existing and emerging vehicle routing problem variants
TL;DR: Vehicle routing problems have been the focus of extensive research over the past sixty years, driven by their economic importance and their theoretical interest as mentioned in this paper, and the diversity of applications has motivated the study of a myriad of problem variants with different attributes.
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•Posted Content
A concise guide to existing and emerging vehicle routing problem variants.
TL;DR: This article provides a concise overview of existing and emerging problem variants of vehicle routing problems and organizes the main problem attributes within this structured framework.
Sentiment analysis and spam detection in short informal text using learning classifier systems
Muhammad Hassan Arif,Jianxin Li,Muhammad Iqbal,Kaixu Liu +3 more
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TL;DR: An existing LCS technique is extended by introducing a novel encoding scheme to represent classifier rules in order to handle the sparseness in feature vectors, which are generated using the term frequency inverse document frequency of word n-grams and sentiment lexicons.
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