Kooperativer Bibliotheksverbund

UID:

Format: XIII, 506 p. 63 illus., 46 illus. in color. , online resource.

Edition: 1st ed. 2024.

ISBN: 9783031576034

Series Statement: International Series in Operations Research & Management Science, 358

Content: Combinatorial Optimization represents a major component of Operations Research, Mathematical Programming, and, in a broader sense, the development of digital intelligence (and society). It covers, in particular, such important areas as network design, location, routing, and scheduling, with major applications in transportation, logistics, health systems, production, communications, and energy. Starting from the exceptional contribution Professor Bernard Gendron made to combinatorial optimization and its applications in multiple areas, the book presents a state-of-the-art view on the field through a combination of surveys, expository articles, and focused methodological and applied research. The authors hail from various Operations Research areas and institutions around the world. Having collaborated closely with Professor Gendron, they drew on his foundational work to showcase a variety of models and algorithms that draw a living picture of the multifaceted word of applied combinatorial optimization.

Note: Bernard Gendron and Operations Research -- Methodological Developments -- Variable Neighbourhood Search with Dynamic Exploration for the Set Union Knapsack Problem -- Common-Flow Formulations for the Diameter Constrained Spanning Tree Problem -- Models and Methods for Two-Level Uncapacitated Facility Location Problem -- Facility Location: A Guide to Modeling and Solving Complex Problem Variants via Lagrangian Relaxation -- Bin Packing Problems for Capacity Planning and Last Mile Applications -- Models for Network Flow and Network Design Problems with Piecewise Linear Costs -- New Formulations for the Scheduled Service Network Design Problem with Piecewise Linear Costs -- Multi-layer Network Design for Consolidation-based Transportation Planning -- Separable Lagrangian Decomposition for Quasi-Separable Problems -- Decomposition-based Algorithms for Mixed-Integer Linear Programs with Integer Subproblems -- Perspectives on Using Benders Decomposition to Solve Two-Stage Stochastic Mixed-Integer Programs -- Decomposition Methods for Choice-Based Optimization Models -- Application-oriented Developments -- The Static Elevator Dispatching Problem with Destination Control -- Flow-based Robustness in Consistent Home Care Service Delivery -- Production Inventory Technician Routing Problem: a Bi-Objective Post-Sales Application -- Express Package Delivery Optimization Using Walkers, Cargo Tricycles and Delivery Trucks -- Integrated Location, Sizing, and Pricing for EV Charging Stations.

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783031576027

Additional Edition: Printed edition: ISBN 9783031576041

Additional Edition: Printed edition: ISBN 9783031576058

Language: English

DOI: 10.1007/978-3-031-57603-4

URL: https://doi.org/10.1007/978-3-031-57603-4

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: 1 online resource (506 pages)

Edition: 1st ed.

ISBN: 3-031-57603-9

Series Statement: International Series in Operations Research and Management Science Series ; v.358

Note: Intro -- Contents -- Bernard Gendron and Operations Research -- 1 Introduction -- 2 Bernard Gendron (1966-2022): Friend and Colleague -- 3 Contents of the Book -- 3.1 Part I: Methodological Developments -- 3.2 Part II: Application-Oriented Developments -- References -- Part I Methodological Developments -- Variable Neighborhood Search with Dynamic Exploration for the Set Union Knapsack Problem -- 1 Introduction -- 2 Main Ingredients of the Variable Neighborhood Search -- 2.1 Constructive Heuristics to Generate Initial Solutions -- 2.2 Neighborhood Structures -- 2.3 Sequential Variable Neighborhood Descent -- 2.4 Shaking Procedure -- 2.5 General Variable Neighborhood Search -- 3 Computational Results -- 3.1 Benchmark Instances -- 3.2 Results with Constructive Heuristics -- 3.3 Results with GVNS -- 3.4 Comparison with I2PLS -- 4 Conclusion -- References -- Common-Flow Formulations for the Diameter Constrained Spanning and Steiner Tree Problems -- 1 Introduction -- 2 Standard Flow-Based Model -- 2.1 Flow-Based Model Based on Pairwise Terminal Connections -- 3 Triangle-Based Models -- 3.1 A Common Flow Realization -- 3.2 An Uncommon Flow Realization -- 4 Computational Results -- 4.1 Comparison of Lower Bounds -- 4.2 Branch-and-Benders Cut Implementations -- 5 Conclusions -- References -- Models and Methods for Two-Level Facility Location Problems -- 1 Introduction -- 2 A Real-Life TUFLP-S with Modular Costs -- 3 Heuristic Approaches for the TUFLP-S with Modular Costs -- 4 Formulations for the TUFLP-S -- 5 Lagrangian-Based Methods for the TUFLP-S -- 6 Conclusions -- References -- Facility Location: A Guide to Modeling and Solving Complex Problem Variants via Lagrangian Relaxation Heuristics -- 1 Introduction -- 2 A Review of Lagrangian Relaxation for Facility Location -- 3 Problem Definition and Mathematical Formulations -- 3.1 A General Model. , 3.2 Special Cases -- 3.3 Accounting for Complex Cost Functions -- 3.4 Accounting for Modular Facility Structures -- 3.5 Accounting for Facility Relocation -- 3.6 Accounting for Uncertainty via 2-Stage Stochastic Programming -- 4 Solution via Lagrangian Relaxation -- 4.1 Solution of the Lagrangian Subproblem -- 4.1.1 Solving the Subproblem for Each Candidate Location -- 4.1.2 Solution in the Case of Complex Cost Functions -- 4.1.3 Solution in the Case of Modular Facility Structures -- 4.1.4 Solution in the Case of Facility Relocation -- 4.1.5 Solution in the Case of Uncertainty via Scenarios -- 4.2 Solution of the Lagrangian Dual Problem -- 4.2.1 Subgradient Method -- 4.2.2 Bundle Methods -- 4.3 Generation of Feasible Upper Bounds -- 4.3.1 Repairing Infeasibility of the Lagrangian Solutions -- 4.3.2 Repairing in the Case of Complex Cost Functions -- 4.3.3 Repairing in the Case of Facility Relocation -- 4.3.4 Repairing in the Case of Uncertainty via Scenarios -- 4.3.5 Improvement Strategies -- 5 Conclusions -- References -- Bin Packing Methodologies for Capacity Planning in Freight Transportation and Logistics -- 1 Introduction -- 2 Packing Problems and Models -- 2.1 Multiple Attribute Packing Problem Extensions -- 2.1.1 Additional Packing Constraints or Attributes -- 2.1.2 Temporal Requirements -- 2.1.3 Uncertainty -- 2.1.4 Multiple Stakeholders -- 2.2 A General Packing Model -- 3 Stakeholders and Capacity Planning in CFTL -- 4 CFTL Capacity Planning with Packing Considerations -- 4.1 Shipper Capacity Planning -- 4.2 Carrier Capacity Planning -- 5 Research Perspectives -- 5.1 Integration of Packing Constraints in Network Capacity Planning -- 5.2 Intensify the Research on Generalizations of Packing Problems -- 5.3 Richer Environments: Multi-Stakeholders, Cooperation, and Competition -- 6 Conclusions -- References. , Models for Network Flow and Network Design Problems with Piecewise Linear Costs -- 1 Introduction -- 2 Notation and Definitions -- 3 Continuous Multicommodity Network Flows -- 3.1 Convex Costs and a Basic Multicommodity Flow Model -- 3.2 The Non-Convex Case and the Multiple Choice Model -- 3.3 The Disaggregated Formulation -- 4 Integer Multicommodity Network Flows -- 4.1 The Point-Based Model -- 4.2 Disaggregating the Point-Based Formulation -- 4.3 Adding Chvátal-Gomory Rank 1 Inequalities -- 5 Unsplittable Multicommodity Network Flows -- 6 Conclusion -- References -- New Formulations for the Scheduled Service Network Design Problem with Piecewise Linear Costs -- 1 Introduction -- 2 The Piecewise-Linear Scheduled Service Network Design Problem: Time-Expanded Network Formulation -- 3 The Consolidation Based Formulation -- 4 Computational Analysis -- 4.1 Instances -- 4.2 Computational Setting -- 4.3 Analysis -- 4.4 Performance of Formulations -- 4.5 Impact of Consoldation Pruning -- 4.6 Comparison to the Classical Model -- 5 Conclusions and Future Work -- References -- Multi-Layer Network Design for Consolidation-Based Transportation Planning -- 1 Introduction -- 2 Multi-Layer Network Design -- 3 MLND Basic Connectivity Requirements and Constraints -- 4 Designing Richer Multilayer Networks -- 4.1 Attribute Connectivity -- 4.2 Multi-Layer Connectivity -- 5 Multi-Layer Network Design for Consolidation-based Freight Transportation Planning -- 5.1 Single-Layer Service Network Design -- 5.2 Two-Layer Service Network Design -- 5.3 Multi-Layer Service Network Design -- 6 Conclusions and Perspectives -- Appendix: Flow Accumulation and Conservation Conformity -- References -- Separable Lagrangian Decomposition for Quasi-Separable Problems -- 1 Introduction -- 2 Master Problem Reformulations for Quasi-Separable Problems -- 2.1 The Master Problem Reformulation. , 2.2 Relationship with Lagrangian Decomposition -- 3 Application to Multicommodity Network Design -- 4 Numerical Experiments -- 5 Conclusions -- References -- Decomposition-Based Algorithms for Mixed-Integer Linear Programs with Integer Subproblems -- 1 Introduction -- 2 Related Work -- 3 Problem Description -- 4 Methodology -- 4.1 Algorithm 1: Alternating Between Classical and Integer Benders Cuts -- 4.2 Algorithm 2: Including Information from the Benders Subproblems in the Master Problem -- 5 Application to Multi-Commodity Facility Location -- 5.1 Benders Decomposition Approach -- 6 Application to Multi-Activity Shift Scheduling -- 6.1 Benders Decomposition Approach -- 7 Numerical Experiments -- 7.1 Results on Multi-Commodity Facility Location Instances -- 7.1.1 Numerical Results -- 7.2 Results on Multi-Activity Shift Scheduling -- 7.2.1 Numerical Results -- 8 Discussion and Concluding Remarks -- References -- Perspectives on Using Benders Decomposition to Solve Two-Stage Stochastic Mixed-Integer Programs -- 1 Introduction -- 2 Benders Decomposition for Two-Stage Stochastic Models -- 3 Partial Benders Decomposition -- 4 Benders Dual Decomposition -- 5 Implementation -- 6 Conclusion -- References -- Decomposition Methods for Choice-Based Optimization Models -- 1 Introduction -- 2 Literature Review -- 2.1 Solution Methods for Transport Problems -- 2.2 Scenario Decomposition for Choice-Based Optimization -- 2.3 Chapter Contributions -- 3 Choice-Based Optimization Framework -- 4 Scenario Decomposition Method -- 4.1 Decomposition by Scenario Groups -- 4.2 Generation of Feasible Solutions -- 4.3 Subgradient Method -- 5 Computational Experiments -- 5.1 Experimental Setting -- 5.2 Performance and Scenario Grouping Strategies -- 5.3 Size of the Scenario Groups -- 5.4 Impact of the Number of Alternatives -- 5.5 Impact of the Number of Individuals. , 6 Decomposition for CBO -- 7 Conclusions -- References -- Part II Application-Oriented Developments -- The Static Elevator Dispatching Problem with Destination Control -- 1 Introduction -- 2 Literature Review -- 3 Problem Description -- 3.1 Additional Rules and Service Order -- 3.2 Problem Data -- 3.3 Objectives -- 3.4 Energy Model -- 4 The Static Elevator Dispatching Problem with Destination Control -- 4.1 The Network Representation -- 4.1.1 Vertices of G -- 4.1.2 Arcs of G -- 4.1.3 Time Costs on A -- 4.1.4 Time Windows -- 4.2 The Optimization Model -- 4.3 Symmetry Breaking and Cuts -- 5 Experiments and Results -- 5.1 Efficiency of Symmetry Breaking and Cuts -- 5.2 Size of the Model -- 5.3 Pareto Frontiers -- 5.4 Running Time According to Parameters -- 5.5 Effect of Saturated Elevator Capacity -- 6 Conclusions and Future Research -- References -- Flow-Based Robustness in Consistent Home Care Service Delivery -- 1 Introduction -- 2 Literature: Uncertainty and Consistency in Home Care -- 3 The Consistent Robust Home Care Problem -- 4 A Flow-Based Mathematical Model -- 4.1 Approximate Robust Formulation -- 4.2 Exact Robust Formulation -- 4.3 Approximate vs Exact Formulation: An Example -- 4.4 Cuts and Valid Inequalities -- 5 Computational Results -- 5.1 Instances, Experimensts and Computing Environment Description -- 5.2 Approximate vs Exact Robust Formulation -- 5.3 Impact of Valid Inequalities -- 6 Conclusions -- Appendix -- References -- Production Inventory Technician Routing Problem:A Bi-objective Post-sales Application -- 1 Introduction -- 2 Problem Description -- 3 Literature Review -- 3.1 Production Routing Problem -- 3.2 Technician Routing and Scheduling Problem -- 3.3 Benders Decomposition -- 4 Problem Formulation -- 5 Solution Procedure -- 6 Computational Experiments -- 7 Conclusions -- References. , Express Package Delivery Optimization Using Walkers, Cargo Tricycles and Delivery Trucks.

Additional Edition: ISBN 3-031-57602-0

Language: English

UID:

Format: 506 Seiten

Edition: 1st ed. 2024

ISBN: 9783031576027

Series Statement: International Series in Operations Research & Management Science 358

Content: Zusammenfassung: Combinatorial Optimization represents a major component of Operations Research, Mathematical Programming, and, in a broader sense, the development of digital intelligence (and society). It covers, in particular, such important areas as network design, location, routing, and scheduling, with major applications in transportation, logistics, health systems, production, communications, and energy. Starting from the exceptional contribution Professor Bernard Gendron made to combinatorial optimization and its applications in multiple areas, the book presents a state-of-the-art view on the field through a combination of surveys, expository articles, and focused methodological and applied research. The authors hail from various Operations Research areas and institutions around the world. Having collaborated closely with Professor Gendron, they drew on his foundational work to showcase a variety of models and algorithms that draw a living picture of the multifaceted word of applied combinatorial optimization

Note: Bernard Gendron and Operations Research -- Methodological Developments -- Variable Neighbourhood Search with Dynamic Exploration for the Set Union Knapsack Problem -- Common-Flow Formulations for the Diameter Constrained Spanning Tree Problem -- Models and Methods for Two-Level Uncapacitated Facility Location Problem -- Facility Location: A Guide to Modeling and Solving Complex Problem Variants via Lagrangian Relaxation -- Bin Packing Problems for Capacity Planning and Last Mile Applications -- Models for Network Flow and Network Design Problems with Piecewise Linear Costs -- New Formulations for the Scheduled Service Network Design Problem with Piecewise Linear Costs -- Multi-layer Network Design for Consolidation-based Transportation Planning -- Separable Lagrangian Decomposition for Quasi-Separable Problems -- Decomposition-based Algorithms for Mixed-Integer Linear Programs with Integer Subproblems -- Perspectives on Using Benders Decomposition to Solve Two-Stage Stochastic Mixed-Integer Programs -- Decomposition Methods for Choice-Based Optimization Models -- Application-oriented Developments -- The Static Elevator Dispatching Problem with Destination Control -- Flow-based Robustness in Consistent Home Care Service Delivery -- Production Inventory Technician Routing Problem: a Bi-Objective Post-Sales Application -- Express Package Delivery Optimization Using Walkers, Cargo Tricycles and Delivery Trucks -- Integrated Location, Sizing, and Pricing for EV Charging Stations

Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-3-031-57603-4

Language: English

Subjects: Economics

Author information: Crainic, Teodor Gabriel