The genetic algorithm method for multiple depot capacitated vehicle routing problem solving

Skok, Minea; Škrlec, Davor; Krajcar, Slavko

doi:10.1109/kes.2000.884102

Cited by 17 publications

(7 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The objective is to determine the sequence of deliveries minimizing the total cost of distribution, which is assumed to be proportional to the distances traveled [15]- [22]. The Multi Depot Vehicle Routing Problem (MD-CVRP), is a variant of the CVRP which assumes multiple depots or storage sites with different locations [23]- [25]. The Vehicle Routing Problem with Time Windows (CVRP-TW), is the variant that assumes the existence of allowable time intervals for the deliverance to each client.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The meta-heuristics that have been applied in the UFT context are ant colony optimization [30], artificial bee colony [34], biogeography-based algorithms [23], the firefly algorithm [19], evolutionary algorithms [15], [17], [18], [24], [25], [31], [21], taboo search [33], [38] and simulated annealing [29], [40], among others. From the articles that address multi-objective versions of VRP with more than 20 nodes (clients), in more than 80% of them use, as said, meta-heuristics, and among them, in particular Evolutionary Multi-Objective Algorithms (MOEAs) [36].…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

A Decision Support Tool for Urban Freight Transport Planning Based on a Multi-Objective Evolutionary Algorithm

et al. 2019

View full text Add to dashboard Cite

We present an optimization procedure based on a hybrid version of an evolutionary multiobjective decision-making algorithm for its application in urban freight transportation planning problems. This tool is intended to solve the planning problems of a merchandise distribution firm that dispatches small volume fractional loads of fresh foods on daily schedules. The firm owns a network of distribution centers supplying a large number of small businesses in Buenos Aires and its surroundings. The recombination operator of the evolutionary algorithm used here has been designed specifically for this problem. It is intended to embody a strategy that takes into account constraints like temporary closeness, closeness time window and connectivity in order to improve its performance in the clustering phase. The representation allows incorporating specific information about the actual instances of the problem and uses adaptive control of the parameters in the calibration stage. The performance of the proposed optimizer was tested against the results obtained by two evolutionary algorithms, NSGA II and SPEA 2, widely used in similar problems. We use hypervolume as a measure of convergence and dispersion of Pareto fronts. The statistical analysis of the results obtained with the three algorithms uses the Wilcoxon rank sum test, which yields evidence that our procedure provides good results.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A Decision Support Tool for Urban Freight Transport Planning Based on a Multi-Objective Evolutionary Algorithm

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Skok et al [14] and Jeon et al [15] used a metaheuristic method to solve MDVRP. Skok et al [14] used general GA with roulette wheel selection in which six crossover operations and three mutation operations were examined.…”

Section: Multi Depot Vrp (Mdvrp)mentioning

confidence: 99%

Solving Rich Vehicle Routing Problem Using Three Steps Heuristic

Editor¹

2019

ijai

View full text Add to dashboard Cite

Vehicle Routing Problem (VRP) relates to the problem of providing optimum service with a fleet of vehicles to customers. It is a combinatorial optimization problem. The objective is usually to maximize the profit of the operation. However, for public transportation owned and operated by the government, accessibility takes priority over profitability. Accessibility usually reduces profit, while increasing profit tends to reduce accessibility. In this research, we look at how accessibility can be increased without penalizing the profitability. This requires the determination of routes with minimum fuel consumption, the maximum number of ports of call and maximum load factor satisfying a number of pre-determined constraints: hard and soft constraints. To solve this problem, we propose a heuristic algorithm. The results from this experiment show that the algorithm proposed has better performance compared to the partitioning set.

show abstract

“…The cycle crossover between the best and the randomly selected parent is proposed in [41] increasing the possibility of retaining the characteristics of the best parent. The repair work after crossover in GA and local search in PSO is totally avoided in [59,52], respectively, by incorporating the penalty coefficient into the objective function. The repair work based on the cost effectiveness is implemented in the work presented in this paper.…”

Section: Related Work On Mtsp/vrpmentioning

confidence: 99%

Probability Collectives: A multi-agent approach for solving combinatorial optimization problems

Kulkarni

Tai

2010

Applied Soft Computing

View full text Add to dashboard Cite

The genetic algorithm method for multiple depot capacitated vehicle routing problem solving

Cited by 17 publications

References 12 publications

A Decision Support Tool for Urban Freight Transport Planning Based on a Multi-Objective Evolutionary Algorithm

A Decision Support Tool for Urban Freight Transport Planning Based on a Multi-Objective Evolutionary Algorithm

Solving Rich Vehicle Routing Problem Using Three Steps Heuristic

Probability Collectives: A multi-agent approach for solving combinatorial optimization problems

Contact Info

Product

Resources

About