- author = "Matija Gulic",
- title = "Parallelization of vehicle routing algorithms by using database with domain-specific embedded functions",
- title2 = "Paralelizacija algoritama za rjesavanje problema usmjeravanja vozila koristenjem baza podataka s ugradenim domenski usmjerenim funkcijama",
- school = "Department of Applied Computing, University of Zagreb",
- year = "2017",
- address = "Croatia",
- keywords = "genetic algorithms, genetic programming, Process Computing",
-
URL = "
https://urn.nsk.hr/urn:nbn:hr:168:300689",
- size = "110 str.",
- abstract = "Increasingly complex variants of the vehicle routing problem with time windows (VRPTW) are coming into focus, alleviated with advances in the computing power. VRPTW is a combination of the classical travelling salesman and bin packing problems, with many real world applications in various fields. From physical resource manipulation planning to virtual resource management in the ever more popular cloud computing domain. The basis for many VRPTW approaches is a heuristic which builds a candidate solution that is subsequently improved by a search or optimization procedure. The choice of the appropriate heuristic may have a great impact on the quality of the obtained results. In this work genetic programming is used to evolve a suitable heuristic to build initial solutions for different objectives and classes of VRPTW instances. Additionally 2-phase parallel algorithm has been proposed to improve initial results obtained by genetic programming. Proposed solution is based on the divide and conquer paradigm, decomposing problem instances into smaller, mutually independent sub-problems which can be solved using traditional algorithms and integrated into a global solution of reasonably good quality. The results show great potential, since this method is applicable to different problem classes and user-defined performance objectives. It has been noticed that sometimes results for vehicle routing problem could not be used in real world applications, due to dynamic behaviour of transport systems (incidents or traffic congestion). Improving traffic control has been studied in this work. Solving traffic congestions represents a high priority issue in many big cities. Traditional traffic control systems are mainly based on pre-programmed, reactive and local techniques. This work presents an autonomic system that uses automated planning techniques instead. These techniques are easily configurable and modified, and can reason about the future implications of actions that change the default traffic lights behaviour. The proposed implemented system includes some autonomic properties, since it monitors the current traffic state, detects whether the system is degrading its performance, sets up new sets of goals to be achieved by the planner, triggers the planner that generates plans with control actions, and executes the selected courses of actions. The obtained results in several artificial and real world data-based simulation scenarios show that the proposed system can efficiently solve traffic congestion.",
- abstract = "Povecanjem brige o okolisu i teznjom za smanjenjem troskova transporta problem usmjeravanja vozila (VRP) postaje sve vaznija stavka u razvijenim drustvima. Navedeni problem je kombinacija nekoliko klasicnih optimizacijskih problema (problem trgovackog putnika, problem pakiranja). U radu je istrazeno nekoliko inovativnih metoda koje bi se mogle primijeniti na sirokom spektru problema iz stvarnog svijeta (prikupljanje otpada, dostava ...). Osnovne poteskoce na koje se nailazi su vrijeme potrebno za pronalazenje prihvatljivih rjesenja i iznimno velik prostor pretrazivanja rjesenja. Kako bi se ostvarilo bolje rezultate od postojecih potrebno je bolje usmjeravanje prilikom pretrazivanja kako se ne bi trosilo vrijeme na istrazivanje nekvalitetnih rjesenja. Koristeci geneticko programiranje i pohlepne funkcije moguce je brzo stvoriti pocetno rjesenje cjelobrojnog problema usmjeravanje vozila s ciljem posluzivanja odredenih lokacija odredenim skupom vozila, te brzo poboljsanje tako dobivenih pocetnih rjesenja. Naknadno poboljsanje pocetnih rjesenja moguce je opisanim paralelnim algoritmima za usmjeravanje vozila. Nakon sto su dobiveni rezultati za problem usmjeravanja vozila, uoceno je da te iste rezultate ponekad nije moguce primijeniti u stvarnom svijetu. Novonastali problem rijesen je stvaranjem jedinstvenog inteligentnog autonomnog prometnog sustava koji ima mogucnosti pratiti stanje prometa, otkriti moguce probleme, promijeniti stanje prometa koristenjem automatiziranog planiranja u cilju ostvarivanja bolje protocnosti prometa. Koristenjem predlozenog sustava pokazano je efikasnije upravljanje prometnim sustavima.",
-
notes = "Language croatian
Universal decimal classification (UDC) 62 URN:NBN urn:nbn:hr:168:300689
Mentor Damir Kalpic",
