diplomska naloga
Erik Dovgan (Avtor), Janez Demšar (Mentor), Bogdan Filipič (Komentor)

Povzetek

Evolucijski algoritem za optimiranje prevoza tovora med dvema lokacijama s skupino vozil

Ključne besede

prevoz tovora;vožnja v koloni;optimiranje prevoza;evolucijski algoritmi;uglaševanje parametrov;metaevolucijski algoritem;požrešna metoda;računalništvo;univerzitetni študij;diplomske naloge;

Podatki

Jezik: Slovenski jezik
Leto izida:
Tipologija: 2.11 - Diplomsko delo
Organizacija: UL FRI - Fakulteta za računalništvo in informatiko
Založnik: [E. Dovgan]
UDK: 004.8:656
COBISS: 22018343 Povezava se bo odprla v novem oknu
Št. ogledov: 1141
Št. prenosov: 300
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Angleški jezik
Sekundarni naslov: [Evolutionary algorithm for optimization of cargo transport between two locations with a group of vehicles]
Sekundarni povzetek: This thesis deals with the optimization of heterogeneous cargo transport between two locations with a group of vehicles. With the increasing size the problem becomes too complex to be solved with deterministic algorithms. Therefore we designed an evolutionary algorithm which belongs to the family of stochastic algorithms. This kind of algorithms is used for solving problems whose solving time with deterministic algorithms would be unacceptable. A disadvantage of stochastic algorithms is that they frequently do not find the optimal solution. Usually they find a suboptimal solution which is a local optimum of the evaluation function. In this thesis we describe the optimization of heterogeneous cargo transport between two locations with a group of vehicles. We begin by formally defining the problem in terms of cargo and vehicle characteristics. Then we present the evolutionary algorithm characteristics and their examples: genetic algorithms, evolutionary strategies, evolutionary programming, genetic programming and differential evolution. Next we describe the evolutionary algorithm implemented to solve the presented problem which was tested with the predefined parameter values on four test problems. The results were compared with those of the greedy algorithm. The evolutionary algorithm mostly found better results than the greedy algorithm. The algorithm parameters were tuned with a metaevolutionary algorithm which is also described. At the end we present the results obtained with the metaevolutionary algorithm, their comparison with the results of the greedy algorithm and the future work.
Sekundarne ključne besede: cargo transport;group transport;transport optimization;evolutionary algorithm;parameter tuning;metaevolutionary algorithm;greedy algorithm;computer science;diploma;
Vrsta datoteke: application/pdf
Vrsta dela (COBISS): Diplomsko delo
Komentar na gradivo: Univerza v Ljubljani, Fakulteta za računalništvo in informatiko
Strani: IX, 46 str.
ID: 24260562