A novel hybrid genetic algorithm for the multidepot periodic vehicle routing problem. Issue 1 (14th July 2014)
- Record Type:
- Journal Article
- Title:
- A novel hybrid genetic algorithm for the multidepot periodic vehicle routing problem. Issue 1 (14th July 2014)
- Main Title:
- A novel hybrid genetic algorithm for the multidepot periodic vehicle routing problem
- Authors:
- Mirabi, Mohammad
- Abstract:
- <abstract abstract-type="normal"> <title>Abstract</title> <p>A genetic algorithm is a metaheuristic proposed to derive approximate solutions for computationally hard problems. In the literature, several successful applications have been reported for graph-based optimization problems, such as scheduling problems. This paper provides one definition of periodic vehicle routing problem for single and multidepots conforming to a wide range of real-world problems and also develops a novel hybrid genetic algorithm to solve it. The proposed hybrid genetic algorithm applies a modified approach to generate a population of initial chromosomes and also uses an improved heuristic called the iterated swap procedure to improve the initial solutions. Moreover, during the implementation a hybrid algorithm, cyclic transfers, an effective class of neighborhood search is applied. The author uses three genetic operators to produce good new offspring. The objective function consists of two terms: total traveled distance at each depot and total waiting time of all customers to take service. Distances are assumed Euclidean or straight line. These conditions are exactly consistent with the real-world situations and have received little attention in the literature. Finally, the experimental results have revealed that the proposed hybrid method can be competitive with the best existing methods as asynchronous parallel heuristic and variable neighborhood search in terms of solution quality to solve the<abstract abstract-type="normal"> <title>Abstract</title> <p>A genetic algorithm is a metaheuristic proposed to derive approximate solutions for computationally hard problems. In the literature, several successful applications have been reported for graph-based optimization problems, such as scheduling problems. This paper provides one definition of periodic vehicle routing problem for single and multidepots conforming to a wide range of real-world problems and also develops a novel hybrid genetic algorithm to solve it. The proposed hybrid genetic algorithm applies a modified approach to generate a population of initial chromosomes and also uses an improved heuristic called the iterated swap procedure to improve the initial solutions. Moreover, during the implementation a hybrid algorithm, cyclic transfers, an effective class of neighborhood search is applied. The author uses three genetic operators to produce good new offspring. The objective function consists of two terms: total traveled distance at each depot and total waiting time of all customers to take service. Distances are assumed Euclidean or straight line. These conditions are exactly consistent with the real-world situations and have received little attention in the literature. Finally, the experimental results have revealed that the proposed hybrid method can be competitive with the best existing methods as asynchronous parallel heuristic and variable neighborhood search in terms of solution quality to solve the vehicle routing problem.</p> </abstract> … (more)
- Is Part Of:
- AI EDAM. Volume 29:Issue 1(2015)
- Journal:
- AI EDAM
- Issue:
- Volume 29:Issue 1(2015)
- Issue Display:
- Volume 29, Issue 1 (2015)
- Year:
- 2015
- Volume:
- 29
- Issue:
- 1
- Issue Sort Value:
- 2015-0029-0001-0000
- Page Start:
- 45
- Page End:
- 54
- Publication Date:
- 2014-07-14
- Subjects:
- Engineering design -- Data processing -- Periodicals
Artificial intelligence -- Periodicals
Expert systems (Computer science) -- Periodicals
620.00420285 - Journal URLs:
- http://www.journals.cambridge.org/jid%5FAIE ↗
- DOI:
- 10.1017/S0890060414000328 ↗
- Languages:
- English
- ISSNs:
- 0890-0604
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 4133.xml