A Novel Algorithm for Capacitated Vehicle Routing Problem for Smart Cities

Sajid, Mohammad; Singh, Jagendra; Haidri, Raza Abbas; Prasad, Mukesh; Vijayakumar, V.; Kotecha, Ketan; Garg, Deepak

doi:10.3390/sym13101923

Cited by 25 publications

(8 citation statements)

References 52 publications

(59 reference statements)

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“…In [24], a giant tour best cost crossover (GTBCX) for the CVRP is proposed. Further, a nondominated sorting GA-II (NSGA-II) utilizing GTBCX is proposed to optimize two objective values in the CVRP, i.e., the overall distance travelled by the given fleet of vehicles and the length of the longest route.…”

Section: Problem Definition: the Cvrpmentioning

confidence: 99%

Genetic Crossover Operators for the Capacitated Vehicle Routing Problem

Ahmed¹,

Alotaibi²,

Al-Tameem³

et al. 2023

Computers, Materials &Amp; Continua

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We study the capacitated vehicle routing problem (CVRP) which is a well-known NP-hard combinatorial optimization problem (COP). The aim of the problem is to serve different customers by a convoy of vehicles starting from a depot so that sum of the routing costs under their capacity constraints is minimized. Since the problem is very complicated, solving the problem using exact methods is almost impossible. So, one has to go for the heuristic/metaheuristic methods and genetic algorithm (GA) is broadly applied metaheuristic method to obtain near optimal solution to such COPs. So, this paper studies GAs to find solution to the problem. Generally, to solve a COP, GAs start with a chromosome set named initial population, and then mainly three operators-selection, crossover and mutation, are applied. Among these three operators, crossover is very crucial in designing and implementing GAs, and hence, numerous crossover operators were developed and applied to different COPs. There are two major kinds of crossover operators-blind crossovers and distance-based crossovers. We intend to compare the performance of four blind crossover and four distance-based crossover operators to test the suitability of the operators to solve the CVRP. These operators were originally proposed for the standard travelling salesman problem (TSP). First, these eight crossovers are illustrated using same parent chromosomes for building offspring(s). Then eight GAs using these eight crossover operators without any mutation operator and another eight GAs using these eight crossover operators with a mutation operator are developed. These GAs are experimented on some benchmark asymmetric and symmetric instances of numerous sizes and various number of vehicles. Our study revealed that the distance-based crossovers are much superior to the blind crossovers. Further, we observed that the sequential constructive crossover with and without mutation operator is the best one for the CVRP. This estimation is validated by Student's t-test at 95% confidence level. We further determined a comparative rank of the eight crossovers for the CVRP.

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Section: Problem Definition: the Cvrpmentioning

confidence: 99%

Genetic Crossover Operators for the Capacitated Vehicle Routing Problem

Ahmed¹,

Alotaibi²,

Al-Tameem³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…The increase in the number of documents about this topic through the last eight years highlights the relevance of this problem [21], reaching the highest number of studies in the year 2021. Perspectives about this problem are related to the use of different and eco-friendly transportation modes, time windows, multiple depots, multi-echelon distribution systems, and split deliveries [22].…”

Section: Vehicle Routing Problem (Vrp)mentioning

confidence: 99%

Urban Logistics through River: A Two-Echelon Distribution Model

2023

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Studies that use rivers in a last-mile delivery context are scarce. This research considers the first multimodal alternative based on a barge for parcel delivery activities. It proposes two sustainable network designs for a two-echelon distribution. The efficiency of scenarios is assessed through performance indicators. A three-stage decomposition heuristic is used. Allocation of the customers to the closest satellite at the first stage uses a non-supervised machine learning clustering method, 2D-k-means. The last two stages, comprising the two echelons routing, are solved using a heuristic based on the nearest neighbor procedure. The fixed costs decrease by 41% and energy consumption by 92% when applying a river transportation mode and e-cargo bikes in the distribution network’s first and second echelon, respectively. Future research avenues are to render the results more realistic with the consideration of other costs and a larger network.

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“…Mohammed et al (2017) used a genetic algorithm (GA) to solve the route of the vehicle routing problem (VRP). Sajid et al (2021) proposed an operator of giant tour best cost crossover for CVRP solutions. Faust et al (2020) used the ant colony optimization (ACO) algorithm with optimized parameters from the GA to compute the CVRP.…”

Section: Related Work In Field Of Capacity-limited Vehicle Routing Pr...mentioning

confidence: 99%

Origin-Oriented Shuffled Frog Leaping Vehicle Routing Multiobjective Optimization Algorithm

Liu

Huo

et al. 2023

Journal of Database Management

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Shuffled frog leaping algorithm is a biological swarm intelligent optimization algorithm and improved into capacity-limited vehicle routing problem. However, the optimization performance is limited with improvement strategies in major of the improvement algorithm. A novel framework of algorithm is proposed to solve capacity-limited vehicle routing problem, including three modules such as origin oriented shuffled frog leaping algorithm strategy, origin oriented shuffled frog leaping vehicle routing multiobjective optimization algorithm strategy, and output module. The frog individuals gather near the origin with the maximum probability and in the area circle, with the frog leaping radius or frog-oriented radius, as the neighborhood. The negative value of the maximum entropy and the shortest total path length of the vehicle are selected as the fitness. The performance test shows that it overcomes the defect of slow convergence compared with other five algorithms. It performs well to solve vehicle routing problems.

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A Novel Algorithm for Capacitated Vehicle Routing Problem for Smart Cities

Cited by 25 publications

References 52 publications

Genetic Crossover Operators for the Capacitated Vehicle Routing Problem

Genetic Crossover Operators for the Capacitated Vehicle Routing Problem

Urban Logistics through River: A Two-Echelon Distribution Model

Origin-Oriented Shuffled Frog Leaping Vehicle Routing Multiobjective Optimization Algorithm

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