Modified Artificial Bee Colony Algorithm for the Capacitated Vehicle Routing Problem

Ding, Hao; Cheng, Hui-jin; Shan, Xian

doi:10.12783/dtssehs/amse2018/24837

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…As a variant of VRP problem, our work is an inherently non-deterministic polynomial (NP-hard) problem, which need to be addressed by heuristic algorithms, such as particle swarm optimization algorithm [44]- [46], genetic algorithm [47], [48], artificial bee colony algorithm [49], [50], fruit fly optimization algorithm [51], [52], tabu search algorithm [53], [54], simulated annealing algorithm [55], [56], The ant colony optimization (ACO) algorithm was first proposed by Dorigo et al [57], it has shown good performance in solving problems such as task assignment and route optimization. The advantages of ACO in real applications have also been demonstrated [58]- [60].…”

Section: B Research On Route Scheduling Optimizationmentioning

confidence: 99%

Marine Cold Chain Transportation Monitoring and Route Scheduling Optimization Based on IoV-BDS

2021

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Recently, the research of the internet of vessels system is a hotspot in the marine engineering area. In this article, the Internet of Vessels based on Beidou satellite navigation system (IoV-BDS) architecture is proposed for marine cold chain transportation monitoring and scheduling. An improved communication method using Beidou short-message communication (SMC) is designed to ensure the reliability of ship-shore data transmission. Additionally, based on the IoV-BDS, we proposed a novel route scheduling optimization model which considers the key costs for marine cold chain transportation, such as fuel, catches damage, and refrigeration energy consumption, and designed a speed selection mechanism. Furthermore, an improved ant colony optimization (IACO) algorithm was utilized to optimize the whole fleet transportation routes, which takes advantage of the A-star algorithm to speed up the convergence of ant colony algorithm (ACO), a novel state transition rule was used to prevent falling into a locally optimal solution. The applicability of IoV-BDS was verified by the shipboard data acquisition and Beidou SMC experiments. The performance evaluation and analysis of route optimization schemes were presented by simulations and comparison with other schemes. The results demonstrated the benefit of our proposed schemes, in terms of solution quality and convergence of the algorithm.INDEX TERMS IoV, Beidou SMC, cold chain, route optimization, refrigerator ship.

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Section: B Research On Route Scheduling Optimizationmentioning

confidence: 99%

Marine Cold Chain Transportation Monitoring and Route Scheduling Optimization Based on IoV-BDS

2021

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“…In previous studies, several types of meta-heuristic algorithms have been carried out to solve CVRP, including Simulated Annealing [7], Genetic Algorithm [8], Particle Swarm Optimization [9], Firefly Algorithm [14], and Artificial Bee Colony [15] [16]. Based on these studies, Artificial Bee Colony (ABC) is one of the meta-heuristic algorithms that can produce the best average solution output.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Artificial Bee Colony and Improved Simulated Annealing for the Capacitated Vehicle Routing Problem

Mar'i

Ubaidillah

Mahmudy

et al. 2022

Knowl. Eng. Data Sci.

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Capacitated Vehicle Routing Problem (CVRP) is a type of NP-Hard combinatorial problem that requires a high computational process. In the case of CVRP, there is an additional constraint in the form of a capacity limit owned by the vehicle, so the complexity of the problem from CVRP is to find the optimum route pattern for minimizing travel costs which are also adjusted to customer demand and vehicle capacity for distribution. One method of solving CVRP can be done by implementing a meta-heuristic algorithm. In this research, two meta-heuristic algorithms have been hybridized: Artificial Bee Colony (ABC) with Improved Simulated Annealing (SA). The motivation behind this idea is to complete the excess and the lack of two algorithms when exploring and exploiting the optimal solution. Hybridization is done by running the ABC algorithm, and then the output solution at this stage will be used as an initial solution for the Improved SA method. Parameter testing for both methods has been carried out to produce an optimal solution. In this study, the test was carried out using the CVRP benchmark dataset generated by Augerat (Dataset 1) and the recent CVRP dataset from Uchoa (Dataset 2). The result shows that hybridizing the ABC algorithm and Improved SA could provide a better solution than the basic ABC without hybridization.

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Modified Artificial Bee Colony Algorithm for the Capacitated Vehicle Routing Problem

Cited by 2 publications

References 8 publications

Marine Cold Chain Transportation Monitoring and Route Scheduling Optimization Based on IoV-BDS

Marine Cold Chain Transportation Monitoring and Route Scheduling Optimization Based on IoV-BDS

Hybrid Artificial Bee Colony and Improved Simulated Annealing for the Capacitated Vehicle Routing Problem

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