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• Which are the most critical nodes in a network? A Basic Variable Neighborhood Search approach.- Variable Neighborhood Descent Branching applied to the Green Electric Vehicle Routing Problem with Time Window and Mixed Fleet.- A Variable Neighborhood Heuristic for Facility Locations in Fog Computing.- A GRASP/VND Heuristic for the Generalized Steiner Problem with Node-Connectivity Constraints and Hostile Reliability.- Max-Diversity Orthogonal Regrouping of MBA Students using a GRASP/VND Heuristic.- Scheduling in parallel machines with two servers: the restrictive case.- Reduced Variable Neighbourhood Search for the generation of controlled circular data.- Sequential and Parallel Scattered Variable Neighborhood Search for Solving Nurikabe.- A Hybrid VNS for the Multi-Product Maritime Inventory Routing Problem.- Simplicial vertex heuristic in solving the Railway arrival and departure paths assignment problem.- Scheduling of Patients in Emergency Departments with a Variable Neighborhood Search.- A GRASP/VND Heuristic for the Heterogeneous Fleet Vehicle Routing Problem with Time Windows.- Using K-means and Variable Neighborhood Search for Automatic Summarization of Scientific Articles.- BVNS approach for the Order Processing in Parallel Picking Workstations .
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This volume constitutes the proceedings of the 8th International Conference on Variable Neighborhood Search, ICVNS 2021, held in Abu Dhabi, United Arab Emirates, in March 2021.The 14 full papers presented in this volume were carefully reviewed and selected from 27 submissions. The papers describe recent advances in methods and applications of variable neighborhood search. Chapter "Reduced Variable Neighbourhood Search for the Generation of Controlled Circular Data" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
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• A Reduced Variable Neighborhood Search Approach for Feature Selection in Cancer Classification.- Basic VNS for a Variant of the Online Order Batching Problem.- A VNS-Based Algorithm for the Mammography Unit Location Problem.- A Hybrid Heuristic Algorithm for the Dial-a-Ride Problem.- Multi-Objective Basic Variable Neighborhood Search for Portfolio Selection.- Local Search Approach for the (r
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This volume constitutes the post- conference proceedings of the 7th International Conference on Variable Neighborhood Search, ICVNS 2019, held in Rabat, Morocco, in October 2019. The 13 full papers presented in this volume were carefully reviewed and selected from 46 submissions. The papers describe recent advances in methods and applications of variable neighborhood search. .
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• Hybrid Metaheuristics: An Introduction.- Combining (Integer) Linear Programming Techniques and Metaheuristics for Combinatorial Optimization.- The Relation Between Complete and Incomplete Search.- Hybridizations of Metaheuristics With Branch & Bound Derivates.- Very Large-Scale Neighborhood Search: Overview and Case Studies on Coloring Problems.- Hybrids of Constructive Metaheuristics and Constraint Programming: A Case Study with ACO.- Hybrid Metaheuristics for Packing Problems.- Hybrid Metaheuristics for Multi-objective Combinatorial Optimization.- Multilevel Refinement for Combinatorial Optimisation: Boosting Metaheuristic Performance.
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Optimization problems are of great importance across a broad range of fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. This book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments. The authors involved in this book are among the top researchers in their domain.
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• Introduction.- Simulated Annealing.- Tabu Search.- Search in Variable Neighborhoods.- The GRASP Search Algorithm.- Evolutionary Algorithms.- Artificial Ants.- Particle Swarms.- Other Metaheuristics.- Other Social Insect Algorithms.- Extending Evolutionary Algorithms for Multiobjective Optimization.- Extending Evolutionary Algorithms for Optimization Under Constraints.- Modeling and Comparison Methods.- Hybrid Metaheuristics for Optimizing Logistics.- Metaheuristics for Vehicle Routing Problems.- Applications in Air Traffic Management.
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Metaheuristics exhibit desirable properties like simplicity, easy parallelizability, and ready applicability to different types of optimization problems. After a comprehensive introduction to the field, the contributed chapters in this book include explanations of the main metaheuristics techniques, including simulated annealing, tabu search, evolutionary algorithms, artificial ants, and particle swarms, followed by chapters that demonstrate their applications to problems such as multiobjective optimization, logistics, vehicle routing, and air traffic management. The authors are leading researchers in this domain, with considerable teaching and applications experience, and the book will be of value to industrial practitioners, graduate students, and research academics.
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• On Monte Carlo Tree Search for Weighted Vertex Coloring.- A RNN-based Hyper-heuristic for combinatorial problems.- Algorithm Selection for the Team Orienteering Problem.- Performance evaluation of a parallel ant colony optimization for the real-time train routing selection problem in large instances.- Deep Infeasibility Exploration Method for Vehicle Routing Problems.- Evolutionary Algorithms for the Constrained Two-Level Role Mining Problem.- Simplifying Dispatching Rules in Genetic Programming for Dynamic Job Shop Scheduling.- Novelty-Driven Binary Particle Swarm Optimisation for Truss Optimisation Problems.- A Beam Search for the Shortest Common Supersequence Problem Guided by an Approximate Expected Length Calculation.- Modeling the Costas Array Problem in QUBO for Quantum Annealing.- Penalty Weights in QUBO formulations: Permutation Problems.- PUBOi: a tunable benchmark with variable importance.- Stagnation Detection meets Fast Mutation.
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This book constitutes the refereed proceedings of the 22nd European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2022, held as part of Evo*2022, in Madrid, Spain, during April 20-21, 2022, co-located with the Evo*2022 events: EvoMUSART, EvoApplications, and EuroGP. The 13 revised full papers presented in this book were carefully reviewed and selected from 28 submissions. They present recent theoretical and experimental advances in combinatorial optimization, evolutionary algorithms, and related research fields.
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• Routing among Convex Polygonal Obstacles in the Plane.- Target Coverage with Minimized Number of Camera Sensors.- Two-Stage Submodular Maximization under Curvature.- An Improved Approximation Algorithm for Capacitated Correlation Clustering Problem.- The Selection of COVID-19 Epidemic Prevention and Control Programs Based on Group Decision Making.- Which Option is a Better Way to Improve Transfer Learning Performance ?.- On Maximizing the Difference between an Approximately Submodular Function and a Linear Function Subject to a Matroid Constraint.- On Various Open-End Bin Packing Game.- A Linear-Time Streaming Algorithm for Cardinality-Constrained Maximizing Monotone Non-submodular Set Functions.- Approximation Algorithms for Two Parallel Dedicated Machine Scheduling with Conflict Constraints.- Computing the One-Visibility Cop-Win Strategies for Trees.- Complexity and Approximation Results on the Shared Transportation Problem.- The complexity of finding optimal subgraphs to represent spatial correlation.- New Approximation Algorithms for the Rooted Budgeted Cycle Cover Problem.- Evolutionary Equilibrium Analysis for Decision on Block Size in Blockchain Systems.- Efficient Algorithms for Scheduling Parallel Jobs with Interval Constraints in Clouds.- Two-Stage Stochastic Max-Weight Independent Set Problems.- Routing and Scheduling Problems with Two Agents on a Line-Shaped Network.- The Price of Anarchy of Generic Valid Utility Systems.- Single Machine Scheduling with Rejection and Generalized Parameters.- Approximation Algorithm and Hardness Results for Defensive Domination in Graphs.- An Improved Physical ZKP for Nonogram.- Finding All Leftmost Separators of Size $\leq k$.- Maximize the Probability of Union-Influenced in Social Networks.- A Novel Algorithm for Max Sat Calling MOCE to Order.- The Smallest Number of Vertices in a 2-Arc-Strong Digraph without Pair of Arc-Disjoint in- and out-Branchings.- Generalized Self-Profit Maximization in Attribute Networks.- Parameterized Complexity Classes Defined by Threshold Circuits: Using Sorting Networks to Show Collapses with W-Hierarchy Classes.- Maximization of Monotone Non-Submodular Functions with a Knapsack Constraint over the Integer Lattice.- Sublinear-time Reductions for Big Data Computing.- Capacitated Partial Inverse Maximum Spanning Tree under the Weighted $l_{\infty}$-Norm.- Approximation Algorithms for Some Min-Max and Minimum Stacker Crane Cover Problems.- Succinct Data Structures for SP, Block-Cactus and 3-Leaf Power Graphs.- Streaming Submodular Maximization under Differential Privacy Noise.- Online Bottleneck Semi-Matching.- Optimal Due Date Assignment without Restriction and Convex Resource Allocation in Group Technology Scheduling.- Constrained Stable Marriage with Free edges or Few Blocking Pairs.- Backgammon is Hard.- Two-Facility Location Games with a Minimum Distance Requirement on a Circle.- Open Shop Scheduling Problem with a Non-Resumable Flexible Maintenance Period.- Parallel Algorithm For Minimum Partial Dominating Set In Unit Disk Graph.- An Improved Approximation Algorithm for Squared Metric k-Facility Location.- Parameterized Algorithms for Linear Layouts of Graphs with Respect to the Vertex Cover Number.- The Fractional k-Truncated Metric Dimension of Graphs.- On Structural Parameterizations of the Offensive Alliance Problem.- On the k-colored Rainbow Sets in Fixed Dimensions.- Cycle-Connected Mixed Graphs and Related Problems.- Directed width parameters on semicomplete digraphs.- Improved Parameterized Approximation for Balanced k-Median.- A LP-Based Approximation Algorithm for Generalized Traveling Salesperson Path Problem.- Hardness Results of Connected Power Domination for Bipartite Graphs and Chordal Graphs.- Approximation Algorithm for Min-Max Correlation Clustering Problem with Outliers.- Delay-Constrained Minimum Shortest Path Trees and Related Problems.- On the Feedback Number of 3-Uniform Linear Extremal Hypergraph.- A Multi-Pass Streaming Algorithm for Regularized Submodular Maximization.
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This book constitutes the refereed proceedings of the 15th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2021, which took place in Tianjin, China, during December 17-19, 2021.The 55 papers presented in this volume were carefully reviewed and selected from 122 submissions. They deal with combinatorial optimization and its applications in general, focusing on algorithms design, theoretical and experimental analysis, and applied research of general algorithmic interest.
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• Cognitive radio networks
• Wireless sensor networks
• Cyber-physical systems
• Distributed and localized algorithm design and analysis
• Information and coding theory for wireless networks
• Localization
• Mobile cloud computing
• Topology control and coverage
• Security and privacy
• Underwater and underground networks
• Vehicular networks
• Information processing and data management
• Programmable service interfaces
• Energy-efficient algorithms
• System and protocol design
• Operating system and middleware support
• Experimental test-beds, models and case studies.

This volume constitutes the proceedings of the 13th International Conference on Combinatorial Optimization and Applications, COCOA 2019, held in Xiamen, China, in December 2019. The 49 full papers presented in this volume were carefully reviewed and selected from 108 submissions. The papers cover the various topics, including cognitive radio networks, wireless sensor networks, cyber-physical systems, distributed and localized algorithm design and analysis, information and coding theory for wireless networks, localization, mobile cloud computing, topology control and coverage, security and privacy, underwater and underground networks, vehicular networks, information processing and data management, programmable service interfaces, energy-efficient algorithms, system and protocol design, operating system and middleware support, and experimental test-beds, models and case studies.

• Supercharging Plant Configurations using Z3
• Why You Should Constrain Your Machine Learned Models
• Contextual Optimization: Bridging Machine Learning and Operations
• A Computational Study of Constraint Programming Approaches for Resource-Constrained Project Scheduling with Autonomous Learning Effects
• Strengthening of feasibility cuts in logic-based Benders decomposition
• Learning Variable Activity Initialisation for Lazy Clause Generation Solvers
• A*-based Compilation of Relaxed Decision Diagrams for the Longest Common Subsequence Problem
• Partitioning Students into Cohorts during COVID-19
• A Two-Phases Exact Algorithm for Optimization of Neural Network Ensemble
• Complete Symmetry Breaking Constraints for the Class of Uniquely Hamiltonian Graphs
• Heavy-Tails and Randomized Restarting Beam Search in Goal-Oriented Neural Sequence Decoding
• Combining Constraint Programming and Temporal Decomposition Approaches
• Scheduling of an Industrial Formulation Plant
• The Traveling Social Golfer Problem: the case of the Volleyball Nations League
• Towards a Compact SAT-based Encoding of Itemset Mining Tasks
• A Pipe Routing Hybrid Approach based on A-Star Search and Linear Programming
• MDDs boost equation solving on discrete dynamical systems
• Variable Ordering for Decision Diagrams: A Portfolio Approach
• Two Deadline Reduction Algorithms for Scheduling Dependent Tasks on Parallel Processors
• Improving the Filtering of Branch-And-Bound MDD solver
• On the Usefulness of Linear Modular Arithmetic in Constraint Programming
• Injecting Domain Knowledge in Neural Networks: a Controlled Experiment on a Constrained Problem
• Learning Surrogate Functions for the Short-Horizon Planning in Same-Day Delivery Problems
• Between Steps: Intermediate Relaxations between big-M and Convex Hull Formulations
• Logic-Based Benders Decomposition for an Inter-modal Transportation Problem
• Checking Constraint Satisfaction
• Finding Subgraphs with Side Constraints
• Short-term scheduling of production fleets in underground mines using CP-based LNS
• Learning to Reduce State-Expanded Networks for Multi-Activity Shift Scheduling
• SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning
• Learning to Sparsify Travelling Salesman Problem Instances
• Optimized Item Selection to Boost Exploration for Recommender Systems
• Improving Branch-and-Bound using Decision Diagrams and Reinforcement Learning
• Physician Scheduling During a Pandemic.

This volume LNCS 12735 constitutes the papers of the 18th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2021, which was held in Vienna, Austria, in 2021. Due to the COVID-19 pandemic the conference was held online. The 30 regular papers presented were carefully reviewed and selected from a total of 75 submissions. The conference program included a Master Class on the topic "Explanation and Verification of Machine Learning Models."

• A Novel Ant Colony Optimization Strategy for the Quantum Circuit Compilation Problem.- Hybridization of Racing Methods with Evolutionary Operators for Simulation Optimization of Traffic Lights Programs.- Decomposition-based Multi-objective Landscape Features and Automated Algorithm Selection.- MATE: A Model-Based Algorithm Tuning Engine.- An Improvement Heuristic Based on Variable Neighborhood Search for a Dynamic Orienteering Problem.- Runtime Analysis of the (mu+1)-EA on the Dynamic BinVal Function.- Tabu-Driven Quantum Neighborhood Samplers.- On Hybrid Heuristics for Steiner Trees on the Plane with Obstacles.- Flowshop NEH-Based Heuristic Recommendation.- Stagnation Detection with Randomized Local Search.- An Artificial Immune System for Black Box Test Case Selection.- Symmetry Breaking for Voting Mechanisms.- A Heuristic Algorithm for School Bus Routing with Bus Stop Selection.- Hybrid Heuristic and Metaheuristic for Solving Electric Vehicle Charging Scheduling Problem.
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This book constitutes the refereed proceedings of the 21st European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2021, held as part of Evo*2021, as Virtual Event, in April 2021, co-located with the Evo*2021 events: EvoMUSART, EvoApplications, and EuroGP. The 14 revised full papers presented in this book were carefully reviewed and selected from 42 submissions. They cover a wide spectrum of topics, ranging from the foundations of evolutionary algorithms and other search heuristics to their accurate design and application to combinatorial optimization problems. Fundamental and methodological aspects deal with runtime analysis, the structural properties of fitness landscapes, the study of core components of metaheuristics, the clever design of their search principles, and their careful selection and configuration. Applications cover problem domains such as scheduling, routing, search-based software engineering and general graph problems. The range of topics covered in this volume reflects the current state of research in the fields of evolutionary computation and combinatorial optimization.
(source: Nielsen Book Data)

• Optimizing Prices and Periods in Time-of-use Electricity Tariff Design Using Bilevel Programming.- An Algebraic Approach for the Search Space of Permutations with Repetition.- A Comparison of Genetic Representations for Multi-Objective Shortest Path Problems on Multigraphs.- The Univariate Marginal Distribution Algorithm Copes well with Deception and Epistasis.- A Beam Search Approach to the Traveling Tournament Problem.- Cooperative Parallel SAT Local Search with Path Relinking.- Dynamic Compartmental Models for Large Multi-Objective Landscapes and Performance Estimation.- Fitness Landscape Analysis of Automated Machine Learning Search Spaces.- On the Combined Impact of Population Size and Sub-problem Selection in MOEA/D.- A Grouping Genetic Algorithm for Multi Depot Pickup and Delivery Problems with Time Windows and Heterogeneous Vehicle Fleets.- MILPIBEA: Algorithm for Multi-Objective Features Selection in (Evolving) Software Product Lines.- A Group Genetic Algorithm for Resource Allocation in Container-Based Clouds.- The Local Optima Level in Chemotherapy Schedule Optimisation.- Genetic Programming with Adaptive Search Based on the Frequency of Features for Dynamic Flexible Job Shop Scheduling.
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This book constitutes the refereed proceedings of the 20th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2020, held as part of Evo*2020, in Seville, Spain, in April 2020, co-located with the Evo*2020 events EuroGP, EvoMUSART and EvoApplications. The 14 full papers presented in this book were carefully reviewed and selected from 37 submissions. The papers cover a wide spectrum of topics, ranging from the foundations of evolutionary computation algorithms and other search heuristics, to their accurate design and application to combinatorial optimization problems.
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• Approximation Algorithms.- Scheduling.- Network Optimization.- Complexity and Logic.- Search, Facility and Graphs.- Geometric Problem.- Sensors, Vehicles and Graphs.- Graph Problems.
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This volume constitutes the proceedings of the 14th International Conference on Combinatorial Optimization and Applications, COCOA 2020, held in Dallas, TX, USA, in December 2020. The 55 full papers presented in this volume were carefully reviewed and selected from 104 submissions. The papers are grouped into the following topics: Approximation Algorithms; Scheduling; Network Optimization; Complexity and Logic; Search, Facility and Graphs; Geometric Problem; Sensors, Vehicles and Graphs; and Graph Problems. Due to the Corona pandemic this event was held virtually.
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• Algorithmic.- Hypergraph Decompositions.- Multi-Agent Path Finding.- New Constraint Programming Model.- On-Demand Multimodal Transit Systems.- Integer programming techniques.- Constrained Clustering.- Deep Neural Networks.- *Inference and relaxation methods.- Innovative applications of CP/AI/OR techniques.
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The volume LNCS 12296 constitutes the papers of the 17th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research which will be held online in September 2020. The 32 regular papers presented together with 4 abstracts of fast-track papers were carefully reviewed and selected from a total of 72 submissions. Additionally, this volume includes the 4 abstracts and 2 invited papers by plenary speakers. The conference program also included a Master Class on the topic "Recent Advances in Optimization Paradigms and Solving Technology".
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This journal publishes on research in hybrid metaheuristics (including evolutionary hybrids) for optimization, control and design in continuous and discrete optimization domains, thereby investigating promising new hybrid algorithmic technologies. Articles published in this journal discuss innovative research on the emergence of cultural artifacts such as game, trade and negotiation strategies and, more generally, rules of behavior as they apply to, for example, robotic, multi-agent and artificial life systems. The journal tries to publish results in Natural Computation, Artificial Intelligence, Machine Learning, Operational Research and Natural Sciences (e.g. cognitive, animal and insect's behavior, etc.) in order to transcend the intrinsic limitations of a single discipline.

• Preface.- Metaheuristic Agent Processes (MAPs).- GRASP with Path-Relinking: Recent advances and applications.- A Tabu Search Heuristic for a University Timetabling Problem.- An Investigation of Automated Planograms Using a Simulated Annealing Based Hyper-Heuristic.- Validation and Optimization of an Elevator Simulation Model with Modern Search Heuristics.- Multi-Objective Hyper-Heuristic Approaches for Space Allocation and Timetabling.- Theory and Practice of the Minimum Shift Design Problem.- Local Search Algorithms for the Two-Dimensional Cutting Stock Problem with a Given Number of Different Patterns.- A Generic Object-Oriented Tabu Search Framework.- Bi-Objective Sequencing of Cutting Patterns: An application for the paper industry.- Metaheuristics Approach for Rule Acquisition in Flexible Shop Scheduling Problems.- Predicting Colorectal Cancer Recurrence: A hybrid neural Networks-based approach.- A Constructive Genetic Approach to Point-Feature Cartographic Label Placement.- Parallel Strategies for GRASP with Path-Relinking.- Speeding Up Local Search Neighborhood Evaluation for a Multi-Dimensional Knapsack Problem.- Computationally Difficult Instances for the Uncapacitated Facility Location Problem.- Consistent Neighborhood in a Tabu Search.- Constraint Oriented Neighborhoods - A New Search Strategy in Metaheuristics.
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Metaheuristics: Progress as Real Problem Solvers is a peer-reviewed volume of eighteen current, cutting-edge papers by leading researchers in the field. Included are an invited paper by F. Glover and G. Kochenberger, which discusses the concept of Metaheuristic agent processes, and a tutorial paper by M.G.C. Resende and C.C. Ribeiro discussing GRASP with path-relinking. Other papers discuss problem-solving approaches to timetabling, automated planograms, elevators, space allocation, shift design, cutting stock, flexible shop scheduling, colorectal cancer and cartography. A final group of methodology papers clarify various aspects of Metaheuristics from the computational view point.
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• On CNF Encodings for Decision Diagrams
• Time-Series Constraints: Improvements and Application in CP and MIP Contexts
• Finding a Collection of MUSes Incrementally
• Decompositions Based on Decision Diagrams
• Logic-Based Decomposition Methods for the Travelling Purchaser Problem
• Lagrangian Decomposition via Subproblem Search
• Non-linear Optimization of Business Models in the Electricity Market
• Weighted Spanning Tree Constraint with Explanations
• Forward-Checking ltering for Nested Cardinality Constraints: Application to an Energy Cost Aware Production Planning Problem for Tissue Manufacturing
• Cyclic Routing of Unmanned Aerial Vehicles
• Parallelizing Constraint Programming with Learning
• Parallel Composition of Scheduling Solvers
• Rail Capacity Planning With Constraint Programming
• Scheduling Home Hospice Care with Logic-Based Benders Decomposition
• A Global Constraint for Mining Sequential Patterns with GAP Constraint
• A Reservoir Balancing Constraint with Applications to Bike-Sharing
• Optimization Models for a Real-World Snow Plow Routing Problem
• The TASKINTERSECTION Constraint
• A Stochastic Continuous Optimization Backend for MiniZinc with Applications to Geometrical Placement Problems
• Constructions and In-place Operations for MDDs Based Constraints
• Balancing Nursing Workload by Constraint Programming
• Designing Spacecraft Command Loops Using Two-Dimension Vehicle Routing
• Constraint Programming Approach for Spatial Packaging Problem
• Detecting Semantic Groups in MIP Models
• Revisiting Two-Sided Stability Constraints
• Optimal Flood Mitigation over Flood Propagation Approximations
• A Bit-Vector Solver with Word Level Propagation
• A New Solver for the Minimum Weighted Vertex Cover Problem
• Optimal Upgrading Schemes for Eective Shortest Paths in Networks.

This book constitutes the proceedings of the 13th International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2016, held in Banff, Canada, in May/June 2016. The 21 full papers presented together with 8 short papers were carefully reviewed and selected from 51 submissions. The conference brings together interested researchers from constraint programming, artificial intelligence, and operations research to present new techniques or applications in combinatorial optimization and provides an opportunity for researchers in one area to learn about techniques in the others, and to show how the integration of techniques from different fields can lead to interesting results on large and complex problems.

• A Computational Study of Neighborhood Operators for Job-shop Scheduling Problems with Regular Objectives.- A Genetic Algorithm for Multi-Component Optimization Problems: the Case of the Travelling Thief Problem.- A Hybrid Feature Selection Algorithm Based on Large Neighborhood Search.- A Memetic Algorithm to Maximise the Employee Substitutability in Personnel Shift Scheduling.- Construct, Merge, Solve and Adapt versus Large Neighborhood Search for Solving the Multi-Dimensional Knapsack Problem: Which One Works Better When.- Decomposing SAT Instances with Pseudo Backbones.- Efficient Consideration of Soft Time Windows in a Large Neighborhood Search for the Districting and Routing Problem for Security Control.- Estimation of Distribution Algorithms for the Firefighter Problem.- LCS-Based Selective Route Exchange Crossover for the Pickup and Delivery Problem with Time Windows.- Multi-rendezvous Spacecraft Trajectory Optimization with Beam P-ACO.- Optimizing Charging Station Locations for Electric Car-Sharing Systems.- Selection of Auxiliary Objectives Using Landscape Features and Offline Learned Classifier.- Sparse, Continuous Policy Representations for Uniform Online Bin Packing via Regression of Interpolants.- The Weighted Independent Domination Problem: ILP Model and Algorithmic .
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This book constitutes the refereed proceedings of the 17th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo*2017 events EuroGP, EvoMUSART and EvoApplications. The 16 revised full papers presented were carefully reviewed and selected from 39 submissions. The papers cover both empirical and theoretical studies on a wide range of academic and real-world applications. The methods include evolutionary and memetic algorithms, large neighborhood search, estimation of distribution algorithms, beam search, ant colony optimization, hyper-heuristics and matheuristics. Applications include both traditional domains, such as knapsack problem, vehicle routing, scheduling problems and SAT; and newer domains such as the traveling thief problem, location planning for car-sharing systems and spacecraft trajectory optimization. Papers also study important concepts such as pseudo-backbones, phase transitions in local optima networks, and the analysis of operators. This wide range of topics makes the EvoCOP proceedings an important source for current research trends in combinatorial optimization.
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• A Hybrid Constructive Mat-Heuristic Algorithm for The Heterogeneous Vehicle Routing Problem with Simultaneous Pick-up and Delivery
• A Property Preserving Method for Extending a Single-Objective Problem Instance to Multiple Objectives with Specific Correlations
• An Evolutionary Approach to the Full Optimization of the Traveling Thief Problem
• Construct, Merge, Solve & Adapt: Application to the Repetition-Free Longest Common Subsequence Problem
• Deconstructing the Big Valley Search Space Hypothesis
• Determining the Difficulty of Landscapes by PageRank Centrality in Local Optima Networks
• Efficient Hill Climber for Multi-Objective Pseudo-Boolean Optimization
• Evaluating Hyperheuristics and Local Search Operators for Periodic Routing Problems
• Evolutionary Algorithms for Finding Short Addition Chains: Going the Distance
• Experimental Evaluation of Two Approaches to Optimal Recombination for Permutation Problems
• Hyperplane Elimination for Quickly Enumerating Local Optima
• Limits to Learning in Reinforcement Learning Hyperheuristics
• Modifying Colourings between Time-Steps to Tackle Changes in Dynamic Random Graphs
• Particle Swarm Optimisation with Sequence-Like Indirect Representation for Web Service Composition
• Particle Swarm Optimization for Multi-Objective Web Service Location Allocation
• Sim-EDA: A Multipopulation Estimation of Distribution Algorithm Based on Problem Similarity
• Solving the Quadratic Assignment Problem with Cooperative Parallel Extremal Optimization.

This book constitutes the refereed proceedings of the 16th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2016, held in Porto, Portugal, in March/April 2016, co-located with the Evo*2015 events EuroGP, EvoMUSART and EvoApplications. The 17 revised full papers presented were carefully reviewed and selected from 44 submissions. The papers cover methodology, applications and theoretical studies. The methods included evolutionary and memetic algorithms, variable neighborhood search, particle swarm optimization, hyperheuristics, mat-heuristic and other adaptive approaches. Applications included both traditional domains, such as graph coloring, vehicle routing, the longest common subsequence problem, the quadratic assignment problem; and new(er) domains such as the traveling thief problem, web service location, and finding short addition chains. The theoretical studies involved fitness landscape analysis, local search and recombination operator analysis, and the big valley search space hypothesis. The consideration of multiple objectives, dynamic and noisy environments was also present in a number of articles.

• Minimum Cardinality Matrix Decomposition into Consecutive-Ones Matrices: CP and IP Approaches.- Connections in Networks: Hardness of Feasibility Versus Optimality.- Modeling the Regular Constraint with Integer Programming.- Hybrid Local Search for Constrained Financial Portfolio Selection Problems.- The "Not-Too-Heavy Spanning Tree" Constraint.- Eliminating Redundant Clauses in SAT Instances.- Cost-Bounded Binary Decision Diagrams for 0-1 Programming.- YIELDS: A Yet Improved Limited Discrepancy Search for CSPs.- A Global Constraint for Total Weighted Completion Time.- Computing Tight Time Windows for RCPSPWET with the Primal-Dual Method.- Necessary Condition for Path Partitioning Constraints.- A Constraint Programming Approach to the Hospitals / Residents Problem.- Best-First AND/OR Search for 0/1 Integer Programming.- A Position-Based Propagator for the Open-Shop Problem.- Directional Interchangeability for Enhancing CSP Solving.- A Continuous Multi-resources cumulative Constraint with Positive-Negative Resource Consumption-Production.- Replenishment Planning for Stochastic Inventory Systems with Shortage Cost.- Preprocessing Expression-Based Constraint Satisfaction Problems for Stochastic Local Search.- The Deviation Constraint.- The Linear Programming Polytope of Binary Constraint Problems with Bounded Tree-Width.- On Boolean Functions Encodable as a Single Linear Pseudo-Boolean Constraint.- Solving a Stochastic Queueing Control Problem with Constraint Programming.- Constrained Clustering Via Concavity Cuts.- Bender's Cuts Guided Large Neighborhood Search for the Traveling Umpire Problem.- A Large Neighborhood Search Heuristic for Graph Coloring.- Generalizations of the Global Cardinality Constraint for Hierarchical Resources.- A Column Generation Based Destructive Lower Bound for Resource Constrained Project Scheduling Problems.
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This book constitutes the refereed proceedings of the 4th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2007, held in Brussels, Belgium in May 2007. It covers methodological and foundational issues from AI, OR, and algorithmics as well as applications to the solution of combinatorial optimization problems in various fields via constraint programming.
(source: Nielsen Book Data)