@conference { ISI:000392439200017,
	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{\textquoteright}16)},
	year = {2016},
	note = {3rd IEEE International Conference on Logistics Operations Management (GOL), Fes, MOROCCO, MAY 23-25, 2016},
	publisher = {Sidi Mohammed Ben Abdellah Univ Fes, Fac Sci \& Technol; Mohammed V Univ Rabat, ENSIAS Sch; Univ Havre; IEEE},
	organization = {Sidi Mohammed Ben Abdellah Univ Fes, Fac Sci \& Technol; Mohammed V Univ Rabat, ENSIAS Sch; Univ Havre; IEEE},
	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 (STCX), and swap mutation operator new individuals are generated. Finally, we give a numerical example on a randomly generated instance to illustrate our approach.},
	isbn = {978-1-4673-8571-8},
	author = {El Bouyahyiouy, Karim and Bellabdaoui, Adil},
	editor = {Alaoui, AE and Benadada, Y and Boukachour, J}
}
