@conference {ElBouyahyiouy2016,
	title = {A new crossover to solve the full truckload vehicle routing problem using genetic algorithm},
	booktitle = {Proceedings of the 3rd IEEE International Conference on Logistics Operations Management, GOL 2016},
	year = {2016},
	note = {cited By 0},
	abstract = {This paper considers the full-truckload selective multi-depot vehicle routing problem under time windows constraints (denoted by FT-SMDVRPTW), which is a generalization of the vehicle routing problem (VRP). Our objective function is to maximize the total profit that the vehicle generates during its trip. In this study, we{\textquoteright}ll present a review of literature about full truckload vehicle routing; we{\textquoteright}ll define the FT-SMDVRPTW that will be resolved via using genetic algorithm. A new complex two-part chromosome is used to represent the solution to our problem. Through a selection based on the elitist method and roulette method, an improved crossover operator called selected two-part chromosome crossover (S-TCX), and swap mutation operator new individuals are generated. Finally, we give a numerical example on a randomly generated instance to illustrate our approach. {\textcopyright} 2016 IEEE.},
	doi = {10.1109/GOL.2016.7731675},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85002262313\&doi=10.1109\%2fGOL.2016.7731675\&partnerID=40\&md5=1920c06e1091fbb7d7c43bf67e4cd65b},
	author = {El Bouyahyiouy, K. and Bellabdaoui, A.}
}
