A Hierarchical Hybrid Meta-Heuristic Approach to Coping with Large Practical Multi-Depot VRP

Shimizu, Yoshiaki; Sakaguchi, Tatsuhiko

doi:10.7232/iems.2014.13.2.163

Cited by 8 publications

(4 citation statements)

References 17 publications

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“…To solve the problem, a heuristic combining the Adaptive Memory Principle and a Tabu Search method was developed. Various heuristic solution methodologies presented by [13], [14], [15], and [16] to solve the MDVRP.…”

Section: Literature Reviewmentioning

confidence: 99%

A Multi-Objective Solution of Green Vehicle Routing Problem

Kabadurmuş

Erdogan

Özkan

et al. 2019

Logistics &Amp; Sustainable Transport

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Distribution is one of the major sources of carbon emissions and this issue has been addressed by Green Vehicle Routing Problem (GVRP). This problem aims to fulfill the demand of a set of customers using a homogeneous fleet of Alternative Fuel Vehicles (AFV) originating from a single depot. The problem also includes a set of Alternative Fuel Stations (AFS) that can serve the AFVs. Since AFVs started to operate very recently, Alternative Fuel Stations servicing them are very few. Therefore, the driving span of the AFVs is very limited. This makes the routing decisions of AFVs more difficult. In this study, we formulated a multi-objective optimization model of Green Vehicle Routing Problem with two conflicting objective functions. While the first objective of our GVRP formulation aims to minimize total CO2 emission, which is proportional to the distance, the second aims to minimize the maximum traveling time of all routes. To solve this multi-objective problem, we used ɛ-constraint method, a multi-objective optimization technique, and found the Pareto optimal solutions. The problem is formulated as a Mixed-Integer Linear Programming (MILP) model in IBM OPL CPLEX. To test our proposed method, we generated two hypothetical but realistic distribution cases in Izmir, Turkey. The first case study focuses on an inner-city distribution in Izmir, and the second case study involves a regional distribution in the Aegean Region of Turkey. We presented the Pareto optimal solutions and showed that there is a tradeoff between the maximum distribution time and carbon emissions. The results showed that routes become shorter, the number of generated routes (and therefore, vehicles) increases and vehicles visit a lower number of fuel stations as the maximum traveling time decreases. We also showed that as maximum traveling time decreases, the solution time significantly decreases.

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Section: Literature Reviewmentioning

confidence: 99%

A Multi-Objective Solution of Green Vehicle Routing Problem

Kabadurmuş

Erdogan

Özkan

et al. 2019

Logistics &Amp; Sustainable Transport

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“…Zhao and Zhang [31] studied online learning based evolutionary many-objective algorithm. Shimizu and Sakaguchi [32] developed hybrid meta heuristic algorithm considering multi depot VRP.…”

Section: Introductionmentioning

confidence: 99%

Vehicle Routing Problem Considering Reconnaissance and Transportation

Kim

Moon

2021

Sustainability

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Troop movement involves transporting military personnel from one location to another using available means. To minimize damage from enemies, the military simultaneously uses reconnaissance and transportation units during troop movements. This paper proposes a vehicle routing problem considering reconnaissance and transportation (VRPCRT) for wartime troop movements. The VRPCRT is formulated as a mixed-integer programming model for minimizing the completion time of wartime troop movements and reconnaissance, and transportation vehicle routes were determined simultaneously in the VRPCRT. For this paper, an ant colony optimization (ACO) algorithm for the VRPCRT was also developed, and computational experiments were conducted to compare the ACO algorithm’s performance and that of the mixed-integer programming model. The performance of the ACO algorithm was shown to yield excellent results even for the real-size problem. Furthermore, a sensitivity analysis of the change in the number of reconnaissance and transportation vehicles was performed, and the effects of each type of vehicle on troop movement were analyzed.

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“…However, in various industrial and business situations having both production and distribution complexities, a feasible solution is not enough and the quality of the solution is also critical. 32 Therefore, exact solution methods are also important. In this direction, to simplify the computational complexity of the mixed-integer optimization problem and obtain the solution with the minimal optimality gap, the concept of the overall time capacity balance has been proposed in an earlier paper on enterprise-wide production and distribution planning of a cryogenic air separation plant.…”

Section: Introductionmentioning

confidence: 99%

“…Further, Bae et al also provide a heuristic algorithm for multidepot VRPTWs, which involves allocating customers for demand fulfillment from several scattered depot locations. However, in various industrial and business situations having both production and distribution complexities, a feasible solution is not enough and the quality of the solution is also critical . Therefore, exact solution methods are also important.…”

Section: Introductionmentioning

confidence: 99%

A Short-Term Planning Framework for the Operation of Tanker-Based Water Distribution Systems in Urban Areas

Maheshwari

Gudi

Subbiah

2020

Ind. Eng. Chem. Res.

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Tanker-based distribution systems have been prevalent in developing countries to supply clean and pure water in different regions. To efficiently operate such tanker service systems, a large fleet of tanker trucks are required to transport water among several water sources, water treatment plants and consumers spanning across the regions. This requires tighter coordination between water suppliers, treatment plant operations, and user groups to use available water resources in a sustainable manner, along with the assurance of water quality and timely delivery. This paper proposes a novel formulation to assist decision-making for optimizing tanker-based water distribution systems and treatment operations, with an overall objective of minimizing the total operating cost such that all of the constraints related to the water demand, supply operations, and environmental and social aspects are honored while supplying water to a maximum number of users. The problem is formulated and solved as a mixed integer linear programming (MILP) optimization framework and captures all of the nuances related to (i) water availability limitations and quality constraints from different sources, (ii) maintaining water quality as it transports via tankers, (iii) water demands for various end-use purposes, and (iv) transportation across a water supply chain. The proposed novel framework is applied to a realistic urban model to find the optimal tanker delivery schedule, ensuring appropriate treatment and timely delivery of water. The results of the case study conducted on a representative-scale problem also elucidate several aspects of treatment plant operation and consumer demand fulfillment for the efficient planning and management of tanker-based water distribution systems.

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A Hierarchical Hybrid Meta-Heuristic Approach to Coping with Large Practical Multi-Depot VRP

Cited by 8 publications

References 17 publications

A Multi-Objective Solution of Green Vehicle Routing Problem

A Multi-Objective Solution of Green Vehicle Routing Problem

Vehicle Routing Problem Considering Reconnaissance and Transportation

A Short-Term Planning Framework for the Operation of Tanker-Based Water Distribution Systems in Urban Areas

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