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Pregled bibliografske jedinice broj: 90699

The Genetic Algorithm Scheduling of Vehicles from Multiple Depots to a Number of Delivery Points


Skok, Minea; Škrlec, Davor; Krajcar, Slavko
The Genetic Algorithm Scheduling of Vehicles from Multiple Depots to a Number of Delivery Points // Advances in Fuzzy Systems and Evolutionary Computation / Nikos Mastorakis (ur.).
New York (NY): World Scientific Publishing ; Engineering Society Press, 2001.


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Naslov
The Genetic Algorithm Scheduling of Vehicles from Multiple Depots to a Number of Delivery Points

Autori
Skok, Minea ; Škrlec, Davor ; Krajcar, Slavko

Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni

Knjiga
Advances in Fuzzy Systems and Evolutionary Computation

Urednik/ci
Nikos Mastorakis

Izdavač
World Scientific Publishing ; Engineering Society Press

Grad
New York (NY)

Godina
2001

Raspon stranica

ISBN
960-8052-27-0

Ključne riječi
non-fixed destination Multiple Depot Capacitated Vehicle Routing Problem, Genetic Algorithm

Sažetak
We develop a new heuristic based on the genetic algorithm (GA) that is used to find high quality solutions to the non-fixed destination Multiple Depot Capacitated Vehicle Routing Problem (MDCVRP) in a reasonable amount of computing time. The definition of the problem with more adherence to reality was proposed. More advanced issues such as solution representation and decoding are developed that enable simultaneous routing of all vehicles. The problem constraints (quantity of goods available at depot, vehicle capacity, maximum route length and maximum number of customers visited in one route) are relaxed using the penalty terms whose parameter values are adjusted during the GA run. Six well-known crossover and three mutation operators developed for the sequencing type representations were compared on fifteen test problems each with different geographical and temporal characteristics. Computational experience one real instance of MDCVRP with 3 depots and 248 customers is discussed that should be didactic illustration of the characteristics and originality of the presented approach.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Projekti:
036016

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Minea Skok (autor)

Avatar Url Davor Škrlec (autor)

Avatar Url Slavko Krajcar (autor)


Citiraj ovu publikaciju:

Skok, Minea; Škrlec, Davor; Krajcar, Slavko
The Genetic Algorithm Scheduling of Vehicles from Multiple Depots to a Number of Delivery Points // Advances in Fuzzy Systems and Evolutionary Computation / Nikos Mastorakis (ur.).
New York (NY): World Scientific Publishing ; Engineering Society Press, 2001.
Skok, M., Škrlec, D. & Krajcar, S. (2001) The Genetic Algorithm Scheduling of Vehicles from Multiple Depots to a Number of Delivery Points. U: Nikos Mastorakis (ur.) Advances in Fuzzy Systems and Evolutionary Computation. New York (NY), World Scientific Publishing ; Engineering Society Press.
@inbook{inbook, author = {Skok, Minea and \v{S}krlec, Davor and Krajcar, Slavko}, year = {2001}, pages = {349}, keywords = {non-fixed destination Multiple Depot Capacitated Vehicle Routing Problem, Genetic Algorithm}, isbn = {960-8052-27-0}, title = {The Genetic Algorithm Scheduling of Vehicles from Multiple Depots to a Number of Delivery Points}, keyword = {non-fixed destination Multiple Depot Capacitated Vehicle Routing Problem, Genetic Algorithm}, publisher = {World Scientific Publishing ; Engineering Society Press}, publisherplace = {New York (NY)} }
@inbook{inbook, author = {Skok, Minea and \v{S}krlec, Davor and Krajcar, Slavko}, year = {2001}, pages = {349}, keywords = {non-fixed destination Multiple Depot Capacitated Vehicle Routing Problem, Genetic Algorithm}, isbn = {960-8052-27-0}, title = {The Genetic Algorithm Scheduling of Vehicles from Multiple Depots to a Number of Delivery Points}, keyword = {non-fixed destination Multiple Depot Capacitated Vehicle Routing Problem, Genetic Algorithm}, publisher = {World Scientific Publishing ; Engineering Society Press}, publisherplace = {New York (NY)} }




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