An Integrated Hub Location and Multi-Depot Vehicle Routing Problem

2013 ◽  
Vol 409-410 ◽  
pp. 1188-1192 ◽  
Author(s):  
Ji Ung Sun
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Solution Method ◽  
Location Problem ◽  
Total System ◽  
Ant Colony Optimization Algorithm ◽  
Hub Location ◽  
Hub Location Problem ◽  
Routing Problem ◽  
Number Of Customers

This paper considers the integrated hub location and multi-depot vehicle routing problem. In this type of problem, we have to determine the location of hubs within a set of candidate locations, allocation of customers to each selected hub location and routes of the vehicles to meet the demands of number of customers in order to minimize the total system cost. To solve these problems simultaneously we apply a hierarchical structure, which hub location as the main problem and vehicle routing as a subordinate one. An integrated solution method based on ant colony optimization algorithm is developed which solves hub location problem and vehicle routing problem hierarchically. Its performance is examined through a comparative study.

An Optimal Design for the Capacitated Hub Location Problem with Asymmetric Allocation

2013 ◽  
Vol 284-287 ◽  
pp. 1203-1207
Author(s):  
Ji Ung Sun
Keyword(s):  
Solution Method ◽  
Location Problem ◽  
Programming Model ◽  
Service Level ◽  
Transportation Costs ◽  
Ant Colony Optimization Algorithm ◽  
Hub Location ◽  
Hub Location Problem ◽  
Hub And Spoke ◽  
Pass Through

Hub and Spoke (H&S) network reflecting the scale economies through consolidation and a large amount of freight transportation is widely used to reduce total transportation costs. H&S network has transportation routes that go to the final delivery point pass through hub linking destination from hub linking origin. In this paper we present a 0-1 integer programming model and a solution method for the capacitated asymmetric allocation hub location problem (CAAHLP). We determine the number of hubs, the locations of hubs, and asymmetric allocation of non-hub nodes to hub with the objective of minimum total transportation costs satisfying the required service level. As the CAAHLP has impractically demanding for the large sized problem, we develop a solution method based on ant colony optimization algorithm. We investigate performance of the proposed solution method through the comparative study. The experimental results show that the newly proposed asymmetrically allocated network can provide better solution than the singly allocated network in terms of cost and service level.

scholarly journals An Endosymbiotic Evolutionary Algorithm for the Hub Location-Routing Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Ji Ung Sun
Keyword(s):  
Evolutionary Algorithm ◽  
Vehicle Routing ◽  
Solution Method ◽  
Programming Model ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub Location Problem ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing

We consider a capacitated hub location-routing problem (HLRP) which combines the hub location problem and multihub vehicle routing decisions. The HLRP not only determines the locations of the capacitatedp-hubs within a set of potential hubs but also deals with the routes of the vehicles to meet the demands of customers. This problem is formulated as a 0-1 mixed integer programming model with the objective of the minimum total cost including routing cost, fixed hub cost, and fixed vehicle cost. As the HLRP has impractically demanding for the large sized problems, we develop a solution method based on the endosymbiotic evolutionary algorithm (EEA) which solves hub location and vehicle routing problem simultaneously. The performance of the proposed algorithm is examined through a comparative study. The experimental results show that the proposed EEA can be a viable solution method for the supply chain network planning.

scholarly journals A more efficient cutting planes approach for the green vehicle routing problem with capacitated alternative fuel stations

2021 ◽  
Author(s):  
Maurizio Bruglieri ◽  
Simona Mancini ◽  
Ornella Pisacane
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Solution Method ◽  
Ad Hoc ◽  
Cutting Plane ◽  
Alternative Fuel ◽  
Routing Problem ◽  
Benchmark Instances ◽  
Number Of Customers ◽  
Fleet Manager

AbstractThe Green Vehicle Routing Problem with Capacitated Alternative Fuel Stations assumes that, at each station, the number of vehicles simultaneously refueling cannot exceed the number of available pumps. The state-of-the-art solution method, based on the generation of all feasible non-dominated paths, performs well only with up to 2 pumps. In fact, it needs cloning the paths between every pair of pumps. To overcome this issue, in this paper, we propose new path-based MILP models without cloning paths, for both the scenario with private stations (i.e., owned by the fleet manager) and that with public stations. Then, a more efficient cutting plane approach is designed for addressing both the scenarios. Numerical results, obtained considering a set of benchmark instances ad hoc generated for this work, show both the efficiency and the effectiveness of this new cutting plane approach proposed. Finally, a sensitivity analysis, carried out by varying the number of customers to be served and their distribution, shows very good performances of the proposed approach.

scholarly journals Current State of Dynamic Vehicle Routing Problems Solved by Ant Colony Optimization Algorithm

2021 ◽  
Vol 15 (3) ◽  
pp. 429-434
Author(s):  
Luka Olivari ◽  
Goran Đukić
Keyword(s):  
Ant Colony Optimization ◽  
Vehicle Routing ◽  
Optimization Algorithm ◽  
Vehicle Routing Problem ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Dynamic Vehicle Routing ◽  
Routing Problems ◽  
Routing Problem ◽  
Solution Methods

Dynamic Vehicle Routing Problem is a more complex version of Vehicle Routing Problem, closer to the present, real-world problems. Heuristic methods are used to solve the problem as Vehicle Routing Problem is NP-hard. Among many different solution methods, the Ant Colony Optimization algorithm is proven to be the efficient solution when dealing with the dynamic version of the problem. Even though this problem is known to the scientific community for decades, the field is extremely active due to technological advancements and the current relevance of the problem. As various sub-types of routing problems and solution methods exist, there is a great number of possible problem-solution combinations and research directions. This paper aims to make a focused review of the current state in the field of Dynamic Vehicle Routing Problems solved by Ant Colony Optimization algorithm, to establish current trends in the field.

scholarly journals On the Selective Vehicle Routing Problem

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 771 ◽  
Author(s):  
Cosmin Sabo ◽  
Petrică C. Pop ◽  
Andrei Horvat-Marc
Keyword(s):  
Mathematical Model ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Mixed Integer ◽  
The Novel ◽  
Routing Problem ◽  
Proposed Model ◽  
Benchmark Instances ◽  
Number Of Customers ◽  
Optimal Set

The Generalized Vehicle Routing Problem (GVRP) is an extension of the classical Vehicle Routing Problem (VRP), in which we are looking for an optimal set of delivery or collection routes from a given depot to a number of customers divided into predefined, mutually exclusive, and exhaustive clusters, visiting exactly one customer from each cluster and fulfilling the capacity restrictions. This paper deals with a more generic version of the GVRP, introduced recently and called Selective Vehicle Routing Problem (SVRP). This problem generalizes the GVRP in the sense that the customers are divided into clusters, but they may belong to one or more clusters. The aim of this work is to describe a novel mixed integer programming based mathematical model of the SVRP. To validate the consistency of the novel mathematical model, a comparison between the proposed model and the existing models from literature is performed, on the existing benchmark instances for SVRP and on a set of additional benchmark instances used in the case of GVRP and adapted for SVRP. The proposed model showed better results against the existing models.

scholarly journals A Heuristic Solution Method for Multi-Depot Vehicle Routing-Based Waste Collection Problems

2020 ◽  
Vol 10 (7) ◽  
pp. 2403
Author(s):  
Yanjun Shi ◽  
Lingling Lv ◽  
Fanyi Hu ◽  
Qiaomei Han
Keyword(s):  
Vehicle Routing ◽  
Waste Disposal ◽  
Vehicle Routing Problem ◽  
Solution Method ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Waste Collection ◽  
Heuristic Solution ◽  
Routing Problem ◽  
Combination Optimization

This paper addresses waste collection problems in which urban household and solid waste are brought from waste collection points to waste disposal plants. The collection of waste from the collection points herein is modeled as a multi-depot vehicle routing problem (MDVRP), aiming at minimizing the total transportation distance. In this study, we propose a heuristic solution method to address this problem. In this method, we firstly assign waste collection points to waste disposal plants according to the nearest distance, then each plant solves the single-vehicle routing problem (VRP) respectively, assigning customers to vehicles and planning the order in which customers are visited by vehicles. In the latter step, we propose the sector combination optimization (SCO) algorithm to generate multiple initial solutions, and then these initial solutions are improved using the merge-head and drop-tail (MHDT) strategy. After a certain number of iterations, the optimal solution in the last generation is reported. Computational experiments on benchmark instances showed that the initial solutions obtained by the sector combination optimization algorithm were more abundant and better than other iterative algorithms using only one solution for initialization, and the solutions with distance gap were obtained using the merge-head and drop-tail strategy in a lower CPU time compared to the Tabu search algorithm.

scholarly journals Dynamic Optimization Model and Algorithm Design for Emergency Materials Dispatch

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Bingbing Dan ◽  
Wanhong Zhu ◽  
Huabing Li ◽  
Yangyang Sang ◽  
Yan Liu
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Algorithm Design ◽  
Time Axis ◽  
Ant Colony Optimization Algorithm ◽  
Dynamic Vehicle Routing ◽  
Routing Problem ◽  
Proposed Model ◽  
Dynamic Optimization Model ◽  
Process Strategy

Emergency materials dispatch (EMD) is a typical dynamic vehicle routing problem (DVRP) and it concentrates on process strategy solving, which is different from the traditional static vehicle routing problem. Based on the characteristics of emergency materials dispatch, DVRP changed the EMD into a series of static problems in time axis. A mathematical multiobjective model is established, and the corresponding improved ant colony optimization algorithm is designed to solve the problem. Finally, a numeric example is provided to demonstrate the validity and feasibility of this proposed model and algorithm.

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