scholarly journals Learning to Approximate Industrial Problems by Operations Research Classic Problems

2021 ◽  
Author(s):  
Axel Parmentier
Keyword(s):  
Operations Research ◽  
Vehicle Routing Problem ◽  
Additional Constraint ◽  
Traveling Salesman ◽  
Structured Learning ◽  
Learning Approach ◽  
Routing Problem ◽  
Classic Problem ◽  
Machine Learning Approach ◽  
Industrial Problem

Operations research (OR) practitioners are accustomed to dealing with variants of classic OR problems. Indeed, an industrial problem often looks like a traveling salesman problem, a vehicle routing problem, a shortest path problem, etc., but has an additional constraint or a different objective that prevent the use of the powerful algorithms produced by decades of research on the classic OR problems. This situation can be frustrating, notably when we realize that the classic problem catches most of the structure of the variant. In “Learning to approximate industrial problems by operations research classic problems,” Axel Parmentier introduces a machine learning approach to use the algorithms for the classic OR problems on the variant. The idea is to leverage structured learning to obtain a mapping that approximates an instance of the variant by an instance of the classic problem.

scholarly journals VEHICLE ROUTING PROBLEM WITH TIME WINDOWS

2014 ◽  
pp. 72-80
Author(s):  
Vladimir Vacic ◽  
Tarek M. Sobh
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Vehicle Routing ◽  
Operations Research ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Traveling Salesman ◽  
Vehicle Routing Problems ◽  
Routing Problem ◽  
Common Problems

The topic of this paper is a Genetic Algorithm solution to the Vehicle Routing Problem with Time Windows, a variant of one of the most common problems in contemporary operations research. The paper will introduce the problem starting with more general Traveling Salesman and Vehicle Routing problems and present some of the prevailing strategies for solving them, focusing on Genetic Algorithms. At the end, it will summarize the Genetic Algorithm solution proposed by K.Q. Zhu which was used in the programming part of the project.

The Traveling Salesman Problem, the Vehicle Routing Problem, and Their Impact on Combinatorial Optimization

2010 ◽  
Vol 1 (2) ◽  
pp. 82-92 ◽  
Author(s):  
Gilbert Laporte
Keyword(s):  
Combinatorial Optimization ◽  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Traveling Salesman ◽  
Routing Problem ◽  
Combinatorial Optimization Problems ◽  
The Traveling Salesman Problem

The Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP) are two of the most popular problems in the field of combinatorial optimization. Due to the study of these two problems, there has been a significant growth in families of exact and heuristic algorithms being used today. The purpose of this paper is to show how their study has fostered developments of the most popular algorithms now applied to the solution of combinatorial optimization problems. These include exact algorithms, classical heuristics and metaheuristics.

scholarly journals Focusing on the Golden Ball Metaheuristic: An Extended Study on a Wider Set of Problems

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
E. Osaba ◽  
F. Diaz ◽  
R. Carballedo ◽  
E. Onieva ◽  
A. Perallos
Keyword(s):  
Genetic Algorithms ◽  
Combinatorial Optimization ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Optimization Problems ◽  
Traveling Salesman ◽  
Routing Problem ◽  
Combinatorial Optimization Problems ◽  
Golden Ball ◽  
The One

Nowadays, the development of new metaheuristics for solving optimization problems is a topic of interest in the scientific community. In the literature, a large number of techniques of this kind can be found. Anyway, there are many recently proposed techniques, such as the artificial bee colony and imperialist competitive algorithm. This paper is focused on one recently published technique, the one called Golden Ball (GB). The GB is a multiple-population metaheuristic based on soccer concepts. Although it was designed to solve combinatorial optimization problems, until now, it has only been tested with two simple routing problems: the traveling salesman problem and the capacitated vehicle routing problem. In this paper, the GB is applied to four different combinatorial optimization problems. Two of them are routing problems, which are more complex than the previously used ones: the asymmetric traveling salesman problem and the vehicle routing problem with backhauls. Additionally, one constraint satisfaction problem (the n-queen problem) and one combinatorial design problem (the one-dimensional bin packing problem) have also been used. The outcomes obtained by GB are compared with the ones got by two different genetic algorithms and two distributed genetic algorithms. Additionally, two statistical tests are conducted to compare these results.

scholarly journals Traveling salesman problem: approach to optimality

2014 ◽  
Vol 15 (2) ◽  
pp. 157-169
Author(s):  
Radosław Jadczak
Keyword(s):  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Decision Problem ◽  
Mathematical Formulation ◽  
Traveling Salesman ◽  
Chinese Postman Problem ◽  
Routing Problem ◽  
Solution Strategies ◽  
Chinese Postman ◽  
Single Vehicle

Abstract Traveling Salesman Problem (TSP) is a basic and one of the most important transportation problems in operational logistics. It is also known in the literature as a Chinese postman problem or single vehicle routing problem. TSP can be shortly described as follows. Vehicle starting from the selected city must visit a set of another cities exactly once and return to the starting city in such a way that the total distance of the route is minimized. In this paper first mathematical formulation of decision problem is presented. Then solution strategies of TSP are shown with selected algorithms as examples. In the last part of article, a computational results of selected methods are presented.

Learning-Based Branch-and-Price Algorithms for the Vehicle Routing Problem with Time Windows and Two-Dimensional Loading Constraints

2021 ◽  
Author(s):  
Xiangyi Zhang ◽  
Lu Chen ◽  
Michel Gendreau ◽  
André Langevin
Keyword(s):  
Vehicle Routing ◽  
Operations Research ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Learning Model ◽  
Exact Algorithms ◽  
Two Dimensional ◽  
Branch And Price ◽  
Routing Problem ◽  
Loading Constraints

A capacitated vehicle routing problem with two-dimensional loading constraints is addressed. Associated with each customer are a set of rectangular items, the total weight of the items, and a time window. Designing exact algorithms for the problem is very challenging because the problem is a combination of two NP-hard problems. An exact branch-and-price algorithm and an approximate counterpart are proposed to solve the problem. We introduce an exact dominance rule and an approximate dominance rule. To cope with the difficulty brought by the loading constraints, a new column generation mechanism boosted by a supervised learning model is proposed. Extensive experiments demonstrate the superiority of integrating the learning model in terms of CPU time and calls of the feasibility checker. Moreover, the branch-and-price algorithms are able to significantly improve the solutions of the existing instances from literature and solve instances with up to 50 customers and 103 items. Summary of Contribution: We wish to submit an original research article entitled “Learning-based branch-and-price algorithms for a vehicle routing problem with time windows and two-dimensional loading constraints” for consideration by IJOC. We confirm that this work is original and has not been published elsewhere, nor is it currently under for publication elsewhere. In this paper, we report a study in which we develop two branch-and-price algorithms with a machine learning model injected to solve a vehicle routing problem integrated the two-dimensional packing. Due to the complexity brought by the integration, studies on exact algorithms in this field are very limited. Our study is important to the field, because we develop an effective method to significantly mitigate computational burden brought by the packing problem so that exactness turns to be achievable within reasonable time budget. The approach can be generalized to the three-dimensional case by simply replacing the packing algorithm. It can also be adapted for other VRPs when high-dimensional loading constraints are concerned. Broadly speaking, the study is a typical example of adopting supervised learning to achieve acceleration for operations research algorithms, which expands the envelop of computing and operations research. Hence, we believe this manuscript is appropriate for publication by IJOC.

An algorithm for the capacitated vehicle routing problem for picking application in manual warehouses

2019 ◽  
Author(s):  
Eleonora Bottani ◽  
Giorgia Casella ◽  
Caterina Caccia ◽  
Roberto Montanari
Keyword(s):  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Order Picking ◽  
Traveling Salesman ◽  
Manhattan Distance ◽  
Routing Problem ◽  
Capacitated Vehicle Routing Problem ◽  
Termination Criteria ◽  
Capacitated Vehicle

Given that warehouses play a central role in modern supply chains, this study proposes the application of an algorithm for the capacitated vehicle routing problem (CVRP) based on the two-index vehicle flow formulation developed by Baldacci, Hadjiconstantinou, and Mingozzi (2004) for picking purposes in manual warehouses. The study of Theys et al. (2010) is first used to represent the warehouse using a Steiner traveling salesman problem (TSP). Then, a calculation of the picking tour’s length is obtained applying the Manhattan distance. Finally, the algorithm for the CVRP is solved through a cutting plane with the addition of termination criteria related to the capacity of picker. The study analyzes four different warehouse configurations, processing five picking list each. The analysis is carried out exploiting the commercial software MATLAB®, to determine the solution that minimize distance of the order picking tour. The results obtained in MATLAB® show the effectiveness of the chosen algorithm applied to the context of manual order picking.

Research on the Optimization of Relief Supplies Distribution Routing Based on Multiple Models

2011 ◽  
Vol 228-229 ◽  
pp. 883-888
Author(s):  
Run Liang Tian ◽  
Peng Yin ◽  
Qin Zhen Li
Keyword(s):  
Vehicle Routing Problem ◽  
Assignment Problem ◽  
Traveling Salesman ◽  
Multiple Models ◽  
Hard Problem ◽  
Planning Model ◽  
Routing Problem ◽  
Np Hard Problem ◽  
Transportation Research ◽  
Uncertain Time

The vehicle routing problem of relief supplies distribution, a typical NP-hard problem, is a hot topic in transportation research. Aiming at a two-echelon supply chain made up of a set of depots and stricken-points, the paper studies the problem how to decide delivery objects and the optimal delivery scheme; This paper decomposes the distribution VRP of relief supplies into an assignment problem and a problem similar to Traveling Salesman Problem, applies the theory of Thiessen Tessellation in spatial analysis to solve the assignment problem. For the sake of the problem of relief supplies distribution with uncertain time, a concept of risk exceeding time has been brought forth, and a multi-layer planning model with the least risk exceeding time has been established, too. At last, an example for this algorithm is given to prove the applicability of the model.

The Traveling Salesman Problem, the Vehicle Routing Problem, and Their Impact on Combinatorial Optimization

2012 ◽  
pp. 342-352
Author(s):  
Gilbert Laporte
Keyword(s):  
Combinatorial Optimization ◽  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Exact Algorithms ◽  
Traveling Salesman ◽  
Routing Problem ◽  
The Traveling Salesman Problem

The Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP) are two of the most popular problems in the field of combinatorial optimization. Due to the study of these two problems, there has been a significant growth in families of exact and heuristic algorithms being used today. The purpose of this paper is to show how their study has fostered developments of the most popular algorithms now applied to the solution of combinatorial optimization problems. These include exact algorithms, classical heuristics and metaheuristics.

scholarly journals Vehicle Routing Optimisation in Humanitarian Operations: A Survey on Modelling and Optimisation Approaches

2021 ◽  
Vol 11 (2) ◽  
pp. 667
Author(s):  
Wadi Khalid Anuar ◽  
Lai Soon Lee ◽  
Stefan Pickl ◽  
Hsin-Vonn Seow
Keyword(s):  
Vehicle Routing ◽  
Operations Research ◽  
Vehicle Routing Problem ◽  
Critical Role ◽  
Routing Problem ◽  
Solution Approach ◽  
Humanitarian Operations ◽  
Hybrid Solutions ◽  
The World ◽  
Model Characteristic

The growing field of humanitarian operations is driven by frequent events of disasters seen in the world today. Within this field, Operations Research (OR) plays a critical role in alleviating the suffering of victims that are impacted by disasters. This paper focuses on the branch of a well-known OR problem, known as the Vehicle Routing Problem (VRP), within the selected scope of humanitarian operations. A total of 123 papers of the last decade are reviewed and classified under the humanitarian operations of supply and delivery, evacuation as well as rescue operations. Besides specific disaster management phases and disaster types, various modelling challenges are highlighted, hinting towards a richer and more complex VRP seen under selected model characteristic classifications. Furthermore, established solution approaches, including hybrid solutions, are highlighted and classified, discussing how they are applied in the context of these humanitarian operations. The inclusion of a machine learning solution approach under the same classification is proposed. Finally, the trend and future outlook of VRP for the suggested humanitarian operations are discussed and highlighted.

Sign in / Sign up

Export Citation Format

Share Document