Two phase genetic algorithm for vehicle routing and scheduling problem with cross-docking and time windows considering customer satisfaction

Baniamerian, Ali; Bashiri, Mahdi; Zabihi, Fahime

doi:10.1007/s40092-017-0203-0

Cited by 34 publications

(16 citation statements)

References 55 publications

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“…For large-size instances, developing a hybrid algorithm provides better results. e genetic algorithm is an intelligent heuristic technique for solving vehicle routing problems by reducing delivery costs significantly, and the following papers prove this: [25][26][27]. us, this paper chooses two well known and proven algorithms to solve the mixed delivery problem efficiently.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

“…e genetic algorithm is a well-known and powerful algorithm to solve different vehicle routing problems, reducing delivery costs significantly by producing better solutions. e following papers are proof of this: [25][26][27]46]. And Branke et al [49] showed that the hybrid algorithm could better reduce logistics costs than simple heuristics by developing an evolutionary algorithm (EA), combining savings heuristic for transport channel selection and vehicle routing problem.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Baniamerian et al [26] solved the cross-docking vehicle routing and scheduling problem focusing on improving customer satisfaction and time windows by developing a mixed-integer programming (MIP) model and a two-phase genetic algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Sadjadi et al [25] solved milk run problem by using the genetic algorithm (GA), and the results indicate that the proposed method significantly reduces the cost of logistics. Baniamerian et al [26] introduced three echelon supply chain problems with cross-docking and proposed a two-phase genetic algorithm (GA) focusing on customer satisfaction. Baniamerian et al [27] studied a heterogeneous vehicle routing problem with cross-docking and developed a hybrid genetic algorithm with modified variable neighborhood search.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Novel Approach for Optimizing the Supply Chain: A Heuristic-Based Hybrid Algorithm

Kocaoğlu

Çakmak

Gümüş

2020

Mathematical Problems in Engineering

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Managing the distribution of goods is a vital operation for many companies. A successful distribution system requires an effective distribution strategy selection and optimum route planning at the right time and minimum cost. Furthermore, customer’s demand and location can vary from order to order. In this situation, a mixed delivery system is a good solution for it and allows the use of different strategies together to decrease delivery costs. Although the “distribution strategy selection” is a critical issue for companies, there are only a few studies that focus on the mixed delivery network problem. There is a need to propose an efficient solution for the mixed delivery problem to guide researchers and practitioners. This paper develops a new “modified” savings-based genetic algorithm which is named “distribution strategy selection and vehicle routing hybrid algorithm (DSSVRHA).” Our new algorithm aims to contribute to the literature a new hybrid solution to solve a mixed delivery network problem that includes three delivery modes: “direct shipment,” “milk run,” and “cross-docking” efficiently. It decides the appropriate distribution strategy and also optimal routes using a heterogeneous fleet of vehicles at minimum cost. The results of the hybrid algorithm are compared with the results of the optimization model. And the performance of the hybrid algorithm is validated with statistical analysis. The computational results reveal that our developed algorithm provides a good solution for reducing the supply chain distribution costs and computational time.

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Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Approach for Optimizing the Supply Chain: A Heuristic-Based Hybrid Algorithm

Kocaoğlu

Çakmak

Gümüş

2020

Mathematical Problems in Engineering

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“…Ross [25], Mousavi [26], and Seyedhoseini [27] proposed cross-dock networks where the cross-dock location varied in response to decisions. Ali [28] proposed the MILP model presented for this problem to increase customer satisfaction by minimizing transportation costs and early/tardy deliveries by scheduling inbound and outbound vehicles. Dondo [29] studied an N-echelon vehicle-routing problem with cross-docking in supply chain management and dealt with the operational management of hybrid multi-echelon distribution networks.…”

Section: Literature Reviewmentioning

confidence: 99%

A Sustainable Multimodal Transport System: The Two-Echelon Location-Routing Problem with Consolidation in the Euro–China Expressway

Lang

et al. 2019

Sustainability

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Sustainable development of transport systems is a common topic of concern and effort in multiple countries, in which reducing carbon emissions is one of the core goals. Multimodal transport is an effective way to achieve carbon emission reduction and to efficiently utilize transport resources. The intercontinental transport system, represented by the Euro–China Expressway, is a prominent exploration that has recently received attention, which promotes the sustainable development of transport between countries and carbon emission reduction. In the intercontinental multimodal transport system, the reasonable connection of roads and railways, especially the optimization of consolidation, is an important link which affects the system's carbon emissions. This paper focuses on the consolidation of sustainable multimodal transport and summarizes the multimodal transport two-echelon location-routing problem with consolidation (MT-2E-LRP-C). We aim to solve multimodal consolidation optimization problem, especially locations of multimodal station, by routing of highway and railway. We propose a two-layer mixed integer linear problem (MILP) model, which highlights the consolidation of roads and railways, focuses on road and rail transport connections, and optimizes road routes and railway schemes. To validate the MT-2E-LRP-C model, we design a series of random instances for different quantities of nodes. In order to solve large-scale instances and realistic transport problems, we propose a hybrid differential evolution algorithm, which decomposes the problem into a railway layer and a highway layer for heuristic algorithm solving. Furthermore, the MILP model and algorithm are tested by small-scale random instances, and the hybrid differential evolution algorithm is solved for the large-scale random instances. Finally, we solve the realist instance from the Euro–China Expressway to develop instructive conclusions.

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Generation of Efficient Cargo Operation Schedule at Seaport with the Use of Multiagent Technologies and Genetic Algorithms

Vasileva

Vladimir

2018

Advances in Intelligent Systems and Computing

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Seaport is a complex economic techno -technological facility. In the modern meaning of this concept it is a specially built and equipped enterprise on the coast, designed for sheltering, loading/unloading and servicing of ships. Information support of such object's operations is a rather difficult informationcomputational task for many reasons -the main one being the generation of an efficient schedule for loading and unloading operations. For these reasons, there is a need to develop an automated system capable of generating an optimal schedule of loading/unloading in a seaport, taking into account the dynamic effect of external factors on its efficient operation. The approach to scheduling is based on multi-agent technologies and a genetic algorithm for generating a schedule for port operation improving the quality of the obtained schedule. It is supposed to use the data received from different agents and corrected during the interaction of such agents. The scheduling is carried out with the genetic algorithms.

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Two phase genetic algorithm for vehicle routing and scheduling problem with cross-docking and time windows considering customer satisfaction

Cited by 34 publications

References 55 publications

A Novel Approach for Optimizing the Supply Chain: A Heuristic-Based Hybrid Algorithm

A Novel Approach for Optimizing the Supply Chain: A Heuristic-Based Hybrid Algorithm

A Sustainable Multimodal Transport System: The Two-Echelon Location-Routing Problem with Consolidation in the Euro–China Expressway

Generation of Efficient Cargo Operation Schedule at Seaport with the Use of Multiagent Technologies and Genetic Algorithms

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