Author
Bruce L. Golden
Other affiliations: Massachusetts Institute of Technology
Bio: Bruce L. Golden is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Vehicle routing problem & Travelling salesman problem. The author has an hindex of 68, co-authored 295 publications receiving 17585 citations. Previous affiliations of Bruce L. Golden include Massachusetts Institute of Technology.
Papers published on a yearly basis
Papers
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01 Jan 2008
TL;DR: In this article, the authors present a survey of the state-of-the-art approaches for solving the Capacitated Vehicle Routing Problem on trees and using a genetic algorithm to solve the generalized orienteering problem.
Abstract: Overviews and Surveys- Routing a Heterogeneous Fleet of Vehicles- A Decade of Capacitated Arc Routing- Inventory Routing- The Period Vehicle Routing Problem and its Extensions- The Split Delivery Vehicle Routing Problem: A Survey- Challenges and Advances in A Priori Routing- Metaheuristics for the Vehicle Routing Problem and Its Extensions: A Categorized Bibliography- Parallel Solution Methods for Vehicle Routing Problems- Recent Developments in Dynamic Vehicle Routing Systems- New Directions in Modeling and Algorithms- Online Vehicle Routing Problems: A Survey- Modeling and Solving the Capacitated Vehicle Routing Problem on Trees- Using a Genetic Algorithm to Solve the Generalized Orienteering Problem- An Integer Linear Programming Local Search for Capacitated Vehicle Routing Problems- Robust Branch-Cut-and-Price Algorithms for Vehicle Routing Problems- Recent Models and Algorithms for One-to-One Pickup and Delivery Problems- One-to-Many-to-One Single Vehicle Pickup and Delivery Problems- Challenges and Opportunities in Attended Home Delivery- Chvatal-Gomory Rank-1 Cuts Used in a Dantzig-Wolfe Decomposition of the Vehicle Routing Problem with Time Windows- Vehicle Routing Problems with Inter-Tour Resource Constraints- From Single-Objective to Multi-Objective Vehicle Routing Problems: Motivations, Case Studies, and Methods- Practical Applications- Vehicle Routing for Small Package Delivery and Pickup Services- Advances in Meter Reading: Heuristic Solution of the Close Enough Traveling Salesman Problem over a Street Network- Multiperiod Planning and Routing on a Rolling Horizon for Field Force Optimization Logistics- Health Care Logistics, Emergency Preparedness, and Disaster Relief: New Challenges for Routing Problems with a Focus on the Austrian Situation- Vehicle Routing Problems and Container Terminal Operations - An Update of Research
976 citations
Book•
01 Jan 1988
TL;DR: Algorithmic Techniques for Vehicle Routing Systems and Models for Complex Routing Environments.
Abstract: Overview. (Contributors: A.A. Assad, B.L. Golden A.A. Assad M. Haimovich, A.H.G. Rinnooy Kan, L. Stougie). Algorithmic Techniques for Vehicle Routing. (Contributors: M. Desrochers, J.K. Lenstra, M.W.P. Savelsbergh, F. Soumis M.M. Solomon, E.K. Baker, J.R. Schaffer K.E. Nygard, P. Greenberg, W.E. Bolkan, E.J. Swenson D.O. Casco, B.L. Golden, E.A. Wasil B. Nag, B.L. Golden, A. Assad). Models for Complex Routing Environments. (Contributors: G. Laporte M.O. Ball H.N. Psaraftis W.B. Powell P. Jaillet, A.R. Odoni M. Fischetti, P. Toth). Practical Applications. (Contributors: J.N. Holt, A.M. Watts L. Levy, L. Bodin R.C. Larson, A. Minkoff, P. Gregory U. Pape B.L. Golden). Development of Vehicle Routing Systems. (Contributors: J.M. Hooban J.-M. Rousseau).
762 citations
TL;DR: In this paper, an effective center-of-gravity heuristic is presented that outperforms heuristics from the literature for orienteering, a sport in which start and end points are specified along with other locations.
Abstract: Orienteering is a sport in which start and end points are specified along with other locations. These other locations have associated scores. Competitors seek to visit, in a fixed amount of time, a subset of these locations on the way from the start point to the end point in order to maximize the total score. An effective center-of-gravity heuristic is presented that outperforms heuristics from the literature.
713 citations
TL;DR: This article describes the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning, and provides insights into widespread and emerging modeling approaches to civil applications of UAVs.
Abstract: Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult-to-access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.
576 citations
TL;DR: The intent in this paper is to define a capacitated arc routing problem, to provide mathematical programming formulations, to perform a computational complexity analysis, and to present an approximate solution strategy for this class of problems.
Abstract: A capacitated node routing problem, known as the vehicle routing or dispatch problem, has been the focus of much research attention On the other hand, capacitated arc routing problems have been comparatively neglected Both classes of problems are extremely rich in theory and applications Our intent in this paper is to define a capacitated arc routing problem, to provide mathematical programming formulations, to perform a computational complexity analysis, and to present an approximate solution strategy for this class of problems In addition, we identify several related routing problems and develop tight lower bounds on the optimal solution
519 citations
Cited by
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Journal Article•
TL;DR: This book by a teacher of statistics (as well as a consultant for "experimenters") is a comprehensive study of the philosophical background for the statistical design of experiment.
Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON
13,333 citations
Book•
01 Jan 1992
TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.
Abstract: 1 GAs: What Are They?.- 2 GAs: How Do They Work?.- 3 GAs: Why Do They Work?.- 4 GAs: Selected Topics.- 5 Binary or Float?.- 6 Fine Local Tuning.- 7 Handling Constraints.- 8 Evolution Strategies and Other Methods.- 9 The Transportation Problem.- 10 The Traveling Salesman Problem.- 11 Evolution Programs for Various Discrete Problems.- 12 Machine Learning.- 13 Evolutionary Programming and Genetic Programming.- 14 A Hierarchy of Evolution Programs.- 15 Evolution Programs and Heuristics.- 16 Conclusions.- Appendix A.- Appendix B.- Appendix C.- Appendix D.- References.
12,212 citations
Book•
30 Jun 2002
TL;DR: This paper presents a meta-anatomy of the multi-Criteria Decision Making process, which aims to provide a scaffolding for the future development of multi-criteria decision-making systems.
Abstract: List of Figures. List of Tables. Preface. Foreword. 1. Basic Concepts. 2. Evolutionary Algorithm MOP Approaches. 3. MOEA Test Suites. 4. MOEA Testing and Analysis. 5. MOEA Theory and Issues. 3. MOEA Theoretical Issues. 6. Applications. 7. MOEA Parallelization. 8. Multi-Criteria Decision Making. 9. Special Topics. 10. Epilog. Appendix A: MOEA Classification and Technique Analysis. Appendix B: MOPs in the Literature. Appendix C: Ptrue & PFtrue for Selected Numeric MOPs. Appendix D: Ptrue & PFtrue for Side-Constrained MOPs. Appendix E: MOEA Software Availability. Appendix F: MOEA-Related Information. Index. References.
5,994 citations
TL;DR: Four key areas of Integer programming are examined from a framework that links the perspectives of artificial intelligence and operations research, and each has characteristics that appear usefully relevant to developments on the horizon.
3,985 citations
TL;DR: This paper considers the design and analysis of algorithms for vehicle routing and scheduling problems with time window constraints and finds that several heuristics performed well in different problem environments; in particular an insertion-type heuristic consistently gave very good results.
Abstract: This paper considers the design and analysis of algorithms for vehicle routing and scheduling problems with time window constraints. Given the intrinsic difficulty of this problem class, approximation methods seem to offer the most promise for practical size problems. After describing a variety of heuristics, we conduct an extensive computational study of their performance. The problem set includes routing and scheduling environments that differ in terms of the type of data used to generate the problems, the percentage of customers with time windows, their tightness and positioning, and the scheduling horizon. We found that several heuristics performed well in different problem environments; in particular an insertion-type heuristic consistently gave very good results.
3,211 citations