Improved Ant Colony System for VRPSPD with Maximum Distance Constraint

Zhang, Tao; Tian, Wen-xin; Zhang, Yuejie; Liu, Shixin

doi:10.1016/s1874-8651(09)60008-9

Cited by 16 publications

(3 citation statements)

References 12 publications

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“…Zhang et al [26] investigate the reverse logistics vehicle routing problem with a single depot, simultaneous distribution and collection of the goods by a homogeneous fleet of vehicles under the restrictions of maximum capacities and maximum distance. They proposed an Ant Colony System (ACS) approach in which the vehicle residual loading capacity is introduced into the heuristic function to consider the dynamic fluctuation of vehicle load.…”

Section: Literature Review and Research Contributionmentioning

confidence: 99%

Improving inbound logistic planning for large-scale real-world routing problems: a novel ant-colony simulation-based optimization

Calabrò

Torrisi

Inturri

et al. 2020

Eur. Transp. Res. Rev.

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This paper presents the first results of an agent-based model aimed at solving a Capacitated Vehicle Routing Problem (CVRP) for inbound logistics using a novel Ant Colony Optimization (ACO) algorithm, developed and implemented in the NetLogo multi-agent modelling environment. The proposed methodology has been applied to the case study of a freight transport and logistics company in South Italy in order to find an optimal set of routes able to transport palletized fruit and vegetables from different farms to the main depot, while minimizing the total distance travelled by trucks. Different scenarios have been analysed and compared with real data provided by the company, by using a set of key performance indicators including the load factor and the number of vehicles used. First results highlight the validity of the method to reduce cost and scheduling and provide useful suggestions for large-size operations of a freight transport service.

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Section: Literature Review and Research Contributionmentioning

confidence: 99%

Improving inbound logistic planning for large-scale real-world routing problems: a novel ant-colony simulation-based optimization

Calabrò

Torrisi

Inturri

et al. 2020

Eur. Transp. Res. Rev.

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“…Several VRPSPD procedures proposed to minimize costs include Simulated Annealing (SA) [22], Discrete firefly algorithm [23], variable neighborhood descent and local search [24], adaptive local search integrated with tabu search [25], iterated local search, and adaptive neighborhood selection [26], and branch and cut algorithm [27]. Several other algorithms were also developed to minimize the cost of VRPSPD distribution, such as Genetic Algorithm (GA) [28], particle swarm optimization (PSO) [29], hybrid chaotic quantum evolutionary algorithm [30], hybrid ant colony optimization (ACO) and tabu search [31], ACO [32], differential evolution algorithm [33], and improve ACO [34]. Several previous studies have a function and objective to minimize distribution costs.…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Yellow Saddle Goatfish Algorithm for Fuel Consumption Vehicle Routing Problem with Simultaneous Pick-up and Delivery Problem

Utama¹,

Fitriani

Amallynda³

et al. 2022

JTI

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Currently, the issue of the fuel crisis has become a global concern. The distribution sector is one of the sectors that consume the most significant fuel. Therefore, an effective procedure for fuel energy efficiency is needed to resolve the routing problem. In addition, the vehicle load must be considered in delivery and pickup at each node. This research proposes the novel Hybrid Yellow Saddle Goatfish Algorithm (HYSGA) algorithm to solve the Fuel Consumption Vehicle Routing Problem Simultaneous Pickup and Delivery (FCVRPSPD) problem. The objective function to be achieved was to minimize fuel costs. This study conducted experiments with HYSGA parameters such as the number of Goatfish, iterations, and the number of goatfish clusters to optimize the FCVRPSPD problem. In addition, a sensitivity analysis was presented to examine the effect of the FCVRPSPD variable on fuel costs. This study also compared the proposed algorithm with several state-of-the-art procedures. The results showed that the parameters of the number of Goatfish and the HYSGA iteration affected fuel costs. Furthermore, based on experiments, the proposed algorithm provided a competitive fuel cost compared to other algorithms.

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“…By combining a local search named variable neighborhood descent algorithm into PSO, Goksal et al [23] presented a heuristic approach for VRPSPD and improved several best known solutions. By analysing the vehicle load fluctuation characteristics, Zhang et al [24] designed a heuristic factor and solved the VRPSPD problem with vehicle travel constraints based on an improved ant colony algorithm. Then Zhang et al [25] studied the VRPSPD with time dependent vehicle routing problems and developed a hybrid algorithm that integrated both ant colony system and tabu search algorithms for solving it.…”

Section: Introductionmentioning

confidence: 99%

A Bee Evolutionary Algorithm for Multiobjective Vehicle Routing Problem with Simultaneous Pickup and Delivery

Gong

Deng

Gong

et al. 2018

Mathematical Problems in Engineering

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A new closed-loop supply chain logistics network of vehicle routing problem with simultaneous pickups and deliveries (VRPSPD) dominated by remanufacturer is constructed, in which the customers are originally divided into three types: distributors, recyclers, and suppliers. Furthermore, the fuel consumption is originally added to the optimization objectives of the proposed VRPSPD. In addition, a bee evolutionary algorithm guiding nondominated sorting genetic algorithm II (BEG-NSGA-II) with a two-stage optimization mechanism is originally designed to solve the proposed VRPSPD model with three optimization objectives: minimum fuel consumption, minimum waiting time, and the shortest delivery distance. The proposed BEG-NSGA-II could conquer the disadvantages of traditional nondominated sorting genetic algorithm II (NSGA-II) and algorithms with a two-stage optimization mechanism. Finally, the validity and feasibility of the proposed model and algorithm are verified by simulating an engineering machinery remanufacturing company's reverse logistics and another three test examples.

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Improved Ant Colony System for VRPSPD with Maximum Distance Constraint

Cited by 16 publications

References 12 publications

Improving inbound logistic planning for large-scale real-world routing problems: a novel ant-colony simulation-based optimization

Improving inbound logistic planning for large-scale real-world routing problems: a novel ant-colony simulation-based optimization

A Novel Hybrid Yellow Saddle Goatfish Algorithm for Fuel Consumption Vehicle Routing Problem with Simultaneous Pick-up and Delivery Problem

A Bee Evolutionary Algorithm for Multiobjective Vehicle Routing Problem with Simultaneous Pickup and Delivery

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