Metaheuristics

Name: Metaheuristics | 14th International Conference, MIC 2022, Syracuse, Italy, July 11-14, 2022, Proceedings
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14th International Conference, MIC 2022, Syracuse, Italy, July 11-14, 2022, Proceedings

Luca Di Gaspero Paola Festa Amir Nakib Mario Pavone(Herausgeber*in)

Springer (Verlag)

Erschienen am 22. Februar 2023

XIV, 571 Seiten

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978-3-031-26504-4 (ISBN)

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Inhalt

Intro
Preface
Organization
Contents
Application of CMSA to the Electric Vehicle Routing Problem with Time Windows, Simultaneous Pickup and Deliveries, and Partial Vehicle Charging
1 Introduction
1.1 Our Contribution
1.2 Organization of the Paper
2 Related Literature
3 Problem Description
4 Adapt-CMSA for the EVRP-TW-SPD
4.1 Solution Representation
4.2 The Adapt-CMSA Algorithm
4.3 Solution Construction
5 Experimental Evaluation
5.1 Computational Results
6 Conclusion and Outlook
References
A BRKGA with Implicit Path-Relinking for the Vehicle Routing Problem with Occasional Drivers and Time Windows
1 Introduction
2 State of the Art
3 The VRPODTW Description
4 Solution Approach Using BRKGA
5 Computational Study
5.1 Instances and Parameter Setting
5.2 Numerical Results
6 Conclusions
References
Metaheuristic Algorithms for UAV Trajectory Optimization in Mobile Networks
1 Introduction
2 Problem Description
3 Solution Methods
3.1 Biased Random-Key Genetic Algorithm
3.2 Simulated Annealing Algorithm
4 Experimental Analysis
4.1 Reference Scenario
4.2 Channel Model
4.3 Automatic Parameter Tuning
4.4 Computational Results
5 Conclusions
References
New Neighborhood Strategies for the Bi-objective Vehicle Routing Problem with Time Windows
1 Introduction
2 Bi-objective Routing Problem with Time Windows
2.1 Multi-objective Optimization
2.2 bVRPTW and Related Works
3 Neighborhood Strategies
3.1 The Baseline MOEA/D
3.2 Strategy of Exploration
3.3 Granularity and Pruning of Neighborhoods
4 Experimental Setup
4.1 The Solomon's Benchmark
4.2 Setup and Tuning
4.3 Experimental Protocol
5 Analysis of Neighborhood Strategies
6 Comparison with State of the Art Algorithms
7 Conclusion
References
Tabu Search with Multiple Decision Levels for Solving Heterogeneous Fleet Pollution Routing Problem
1 Introduction
2 Problem Description
3 Literature Review
4 Proposed Solution Methodology
4.1 Measurement of Emissions
4.2 Heterogeneous Fleet
4.3 Initial Solution
4.4 Coding and Decoding
4.5 Tabu Search Proposed
5 Results
6 Conclusions
References
A Learning Metaheuristic Algorithm for a Scheduling Application
1 Introduction
2 Related Literature
3 Problem Statement and Proposed Learning Algorithm
4 Experiments
5 Discussion
6 Conclusion
References
MineReduce-Based Metaheuristic for the Minimum Latency Problem
1 Introduction
2 The Minimum Latency Problem
3 The MDM-GILS-RVND Metaheuristic
4 MineReduce-Based Metaheuristic for the MLP
4.1 The MineReduce Approach
4.2 MineReduce-Based GILS-RVND
5 Computational Results
6 Conclusion
References
Optimizing Multi-variable Time Series Forecasting Using Metaheuristics
1 Introduction
2 Method, Model and Optimization
2.1 Model
2.2 Configuration
2.3 Optimization
3 Results
4 Conclusions and Future Works
References
Unsupervised Machine Learning for the Quadratic Assignment Problem
1 Introduction
2 Technical Background
2.1 The Quadratic Assignment Problem
2.2 Frequent Itemsets in Associative Rule Learning
3 Frequent Itemsets for Local Search Algorithms
3.1 Extraction and Combination of Frequent Itemsets
3.2 Apriori Algorithm for Extracting Itemsets from a Set of Solutions
3.3 Combining Itemsets for Creating a New Set of Solutions
4 Performance Evaluation
4.1 QAP Instances
4.2 Parameters for the Experiments
4.3 Quality of Solutions
4.4 Additional Information for the Positions of Solutions
5 Conclusions
References
On Optimizing the Structure of Neural Networks Through a Compact Codification of Their Architecture
1 Introduction
2 Proposed Methodology
2.1 Teaching-Learning-Based Optimization (TLBO)
2.2 Solution Encoding
2.3 Cost Function
3 Application Example
4 Experimentation and Results
5 Conclusions
References
Neural Architecture Search Using Differential Evolution in MAML Framework for Few-Shot Classification Problems
1 Introduction
2 Neural Architecture Search in MAML
2.1 Neural Architecture Search
2.2 MAML Framework
2.3 Differential Evolution
3 Experimental Setting
3.1 Datasets
3.2 Training and Evaluation
3.3 Search Space for MAML
3.4 Architecture Encoding and DE Parameters
4 Results and Discussion
5 Conclusion
References
Neural Architecture Search Using Metaheuristics for Automated Cell Segmentation
1 Introduction
2 Methodologies
2.1 Search Space
2.2 Architecture Encoding
2.3 Metaheuristics
3 Experimental Setup
3.1 Data Set
4 Results and Discussion
5 Conclusion
References
Analytical Methods to Separately Evaluate Convergence and Diversity for Multi-objective Optimization
1 Introduction
2 Conventional Performance Indicators
2.1 Hypervolume
2.2 Inverted Generational Distance
2.3 Generational Distance
3 Proposed Analytical Methods
3.1 Diversity Indicators
3.2 Proposed Methods for Comparison and Visualization
4 Computational Experiments
4.1 Analysis for Many-Objective MaF7 Problems
4.2 Analysis for a Three-Objective DTLZ Test Suite
5 Conclusion
References
How a Different Ant Behavior Affects on the Performance of the Whole Colony
1 Introduction
2 The Model
3 Experiments and Results
3.1 Group Analysis
3.2 Overall Analysis
4 Conclusions
References
Evaluating the Effects of Chaos in Variable Neighbourhood Search
1 Introduction
2 Related Work
3 The Labelled Spanning Tree and Forest Problems
4 Variable Neighbourhood Search
5 Using Chaos in VNS
6 Experimental Results
7 Conclusions
References
Investigating Fractal Decomposition Based Algorithm on Low-Dimensional Continuous Optimization Problems
1 Introduction
2 Related Work
3 The Fractal Decomposition Based Algorithm
3.1 Exploration Component
3.2 Exploitation Component
4 Benchmark
4.1 Performance Metrics
5 Experiments and Discussion
5.1 Runtime Distributions (ECDFs) Summary and Function Groups
5.2 Scaling of Runtime with Problem Dimension
5.3 Discussion
6 Conclusions
References
A Comparative Analysis of Different Multilevel Approaches for Community Detection
1 Introduction
2 The Modularity as Evaluation Metric
3 Immune Metaheuristics
4 Multi-level Approaches
4.1 Random and Smart Explosion
4.2 Smart Merge
5 Experimental Results
6 Conclusions and Future Work
References
Tchebycheff Fractal Decomposition Algorithm for Bi-objective Optimization Problems
1 Introduction
2 Reference Points in Decomposition-Based Algorithms
3 The Fractal Tchebycheff Algorithm
3.1 Regularisation of the Tchebycheff Fractal
3.2 Dynamic Management of the Fractal Distribution
4 Computational Experiments
4.1 Numerical Results
5 Conclusion and Perspectives
References
Local Search for Integrated Predictive Maintenance and Scheduling in Flow-Shop
1 Introduction
2 Problem Definition
3 Mathematical Model
4 Solution Method
4.1 Local Search
4.2 Simulated Annealing
5 Experimental Analysis
5.1 Instance Generator
5.2 Parameter Tuning
5.3 Experimental Results
6 Conclusions
References
An Investigation of Hyper-Heuristic Approaches for Teeth Scheduling
1 Introduction
2 The Artificial Teeth Scheduling Problem
3 Low-Level Heuristics for the ATSP
4 Experimental Evaluation
5 Conclusion
References
A Mixed-Integer Programming Formulation and Heuristics for an Integrated Production Planning and Scheduling Problem
1 Introduction
2 Related Works
3 Mixed-Integer Programming Formulation
4 MIP Heuristics for CLSP-HFS Problem
4.1 Relax-and-Fix (RF)
4.2 Fix-and-Optimize (FO)
4.3 Relax-and-Fix-and-Optimize (RFO)
5 Decomposition Strategies
6 Numerical Experiments
7 Conclusions
References
Construct, Merge, Solve and Adapt Applied to the Maximum Disjoint Dominating Sets Problem
1 Introduction
2 Related Work
3 Graphical Problem Illustration
4 The CMSA Approach to the MDDSP
4.1 Lexicographic Objective Function
4.2 The CMSA Algorithm
5 Experimental Evaluation
5.1 Problem Instances
5.2 Parameters Tuning
5.3 Results
6 Conclusions
References
Fixed Set Search Applied to the Territory Design Problem
1 Introduction
2 Related Research
3 Model
4 Heuristic
5 Computational Study
6 Conclusions
References
The P-Next Center Problem with Capacity and Coverage Radius Constraints: Model and Heuristics
1 Introduction
2 Related Work and Problem Formulation
2.1 Related Work
2.2 Problem Formulation
3 Customizing the BRKGA for the pNCPCR
3.1 Evolutionary Process
3.2 Chromosome Representation and Decoder
4 Experimental Results
4.1 Instances
4.2 Computational Environment and Parameter Settings
4.3 Mathematical Model Results
4.4 BRKGA Results
5 Conclusions
References
Automatic Configuration of Metaheuristics for Solving the Quadratic Three-Dimensional Assignment Problem Using Irace
1 Introduction
2 The Q3AP
3 Metaheuristics for the Q3AP
3.1 Particle Swarm Optimization for Q3AP
3.2 TS for Q3AP
3.3 ILS for Q3AP
3.4 PSO-TS and PSO-ILS for Q3AP
4 Automated Algorithm Configuration
4.1 The Automatic Configuration of Algorithms
4.2 Parameters Configuration
5 Experimental Evaluation
5.1 Experimental Setup
5.2 Experimental Results
6 Conclusion
References
Hyper-parameter Optimization Using Continuation Algorithms
1 Introduction
2 Related Work
3 Hyper-parameter Optimization via Continuation
4 Our Continuation Approach for Hyper-parameter Optimization
5 Results and Discussion
5.1 Accuracy Analysis
5.2 Additional Meta-parameters
6 Conclusions
References
Selecting the Parameters of an Evolutionary Algorithm for the Generation of Phenotypically Accurate Fractal Patterns
1 Introduction
1.1 Overview of the Paper
2 Problem Specification
2.1 Selected Fractal: The Barnsley Fern
2.2 GA Parameters
3 Results and Evaluation
4 Conclusions and Future Work
References
Addressing Sustainability in Precision Agriculture via Multi-Objective Factored Evolutionary Algorithms
1 Introduction
2 Background
2.1 Prescription Maps
2.2 Multi-Objective Optimization
3 Related Work
4 Optimizing Prescriptions with MO-FEA and NSGA-II
5 General Experimental Approach
5.1 Factor Architecture
5.2 Objective Functions
5.3 Evaluation Metrics
5.4 Prescription Evaluation
6 Experimental Prescription Results
6.1 Parameters and Data
6.2 Results and Discussion
7 Optimal Prescription Results
7.1 Parameters and Data
7.2 Results and Discussion
8 Conclusion
9 Future Work
References
Modeling and Solving the K-Track Assignment Problem
1 Introduction
2 Solver-Independent Modeling Approaches for the K-Track Assignment Problem
2.1 Constraint Programming Model
2.2 Integer Linear Programming Model
2.3 Network Flow Reformulation
3 A Simulated Annealing Approach
4 Computational Results
4.1 Generation of Instances
4.2 Comparison of Results
4.3 Comparison to the Literature
4.4 The Deployment of Our Method on Real-Life Scenarios
5 Conclusion
References
Instance Space Analysis for the Generalized Assignment Problem
1 Introduction
2 Problem Definition
3 Related Work
4 Algorithms
5 Instances
5.1 Results on Existing Instances
5.2 Extended Instance Set
6 Instance Space Analysis
6.1 Concept and Methodology
6.2 Performance Measure
6.3 Features
6.4 Initial Instance Space Analysis
6.5 New Instance Generator
6.6 Instance Space Analysis for the Full Instance Set
7 Conclusion
References
Decision Support for Agri-Food Supply Chains in the E-Commerce Era: The Inbound Inventory Routing Problem with Perishable Products
1 Introduction
2 Literature Review
3 Problem Definition and Mathematical Formulation
4 A Two-Stage Matheuristic Decomposition
4.1 Stage 1 - Solving Purchasing and Inventory Decisions
4.2 Stage 2 - Routing Decisions
4.3 Connection Between Stages
5 Computational Experiments
5.1 Data Sets
5.2 Stopping Condition
5.3 Results
6 Conclusions
References
A Multi-objective Biased Random-Key Genetic Algorithm for the Siting of Emergency Vehicles
1 Introduction
2 Methods
2.1 Study Area
2.2 Biased Random-Key Genetic Algorithm
3 Preliminary Results
4 Conclusion
References
Simulated Annealing for a Complex Industrial Scheduling Problem
1 Introduction
2 Description of the Problem
3 Neighbourhood-Based Resolution Approach
3.1 Neighbourhoods Based on the Graph Representation
3.2 Simulated Annealing
4 Experiments and Results
5 Conclusion
References
A Matheuristic for Multi-Depot Multi-Trip Vehicle Routing Problems
1 Introduction
2 Mathematical Formulation
3 A Model Based Matheuristic Framework
4 Computational Results and Discussion
References
Comparing QUBO Models of the Magic Square Problem for Quantum Annealing
1 Introduction
2 The Magic Square Problem
3 One-Hot Encoding
4 Unary/Domain-Wall Encoding
5 Experiments with Fixstars Amplify Digital Annealer
6 Conclusion
References
Self-adaptive Publish/Subscribe Network Design
1 The Publish/Subscribe Pattern
2 The Lagrangian Matheuristic
3 Preliminary Computational Results
References
An Efficient Fixed Set Search for the Covering Location with Interconnected Facilities Problem
1 Introduction
2 Problem Description
3 Fixed Set Search
4 Computational Results
5 Conclusion
References
Hybrid PSO/GA+solver Approaches for a Bilevel Optimization Model to Optimize Electricity Dynamic Tariffs
1 Introduction
2 A Bilevel Nonlinear Optimization Model to Optimize Electricity Dynamic Tariffs
3 Hybrid PSO+solver and GA+solver Approaches
3.1 Results
4 Conclusion
References
An Agent-Based Model of Follow-the-leader Search Using Multiple Leaders
1 Introduction
2 Methods and Materials
2.1 Algorithm Design
2.2 Model Implementation
3 Empirical Study
4 Conclusions
References
A Scatter Search Approach for the Parallel Row Ordering Problem
1 Introduction and Problem Description
2 Algorithmic Proposal
2.1 Scatter Search
2.2 Combination Method
3 Experimental Experience
3.1 Proposal Tuning
3.2 Results
4 Conclusions and Future Work
References
A Multi-Population BRKGA for Energy-Efficient Job Shop Scheduling with Speed Adjustable Machines
1 Introduction
2 Problem Definition
3 The Proposed Multi-objective MpBRKGA
4 Numerical Results
5 Conclusion
References
An Evolutionary Algorithm Applied to the Bi-Objective Travelling Salesman Problem
1 Introduction
2 Base Algorithms
2.1 Biased Random-Key Genetic Algorithms
2.2 Elitist Non-dominated Sorting Genetic Algorithm
3 Non-dominated Sorting Biased Random-Key Genetic Algorithm
4 Bi-Objective Travelling Salesman Problem
5 Computational Experiments
References
Hybrid Metaheuristic Approaches for Makespan Minimization on a Batch Processing Machine
1 Introduction
2 Metaheuristic Approaches
3 Computational Experimentation
4 Conclusions
References
Variable Neighborhood Descent for Software Quality Optimization
1 Introduction
2 Problem Definition
3 Algorithmic Proposal
4 Experimental Results
References
Iterated Local Search with Genetic Algorithms for the Photo Slideshow Problem
1 Introduction
2 Mathematical Formulation
3 Solution Approach
3.1 Preprocessing, Search Space and Fitness Function
3.2 Initial Solution and Neighborhood Structure
3.3 Iterated Local Search with Genetic Algorithms
4 Computational Experiments
4.1 Data Set and Parameter Tuning
4.2 Comparison Results
5 Conclusion and Future Work
References
A Tabu Search Matheuristic for the Generalized Quadratic Assignment Problem
1 Introduction
2 Modelling the GQAP
3 Solving the GQAP with TS-GQAP
3.1 Basic Concepts
3.2 Implementation Details
4 Computational Results
5 Summary, Criticism and Outlook
References
A Fast Metaheuristic for Finding the Minimum Dominating Set in Graphs
1 Introduction
2 Greedy Randomized Adaptive Search Procedure
2.1 Construction
2.2 Local Improvement
3 Computational Experiments
4 Conclusion
References
Scheduling Jobs in Flexible Flow Shops with s-batching Machines Using Metaheuristics
1 Introduction
2 Problem Setting and Related Work
2.1 Problem Description
2.2 Discussion of Previous Work
3 Metaheuristic Approaches
3.1 Iterative Decomposition Scheme
3.2 GGA for Solving the Subproblems
3.3 ILS for Solving the Subproblems
4 Computational Experiments
5 Conclusions and Future Research
Appendix A: MILP Formulation
Appendix B: Design of Experiments
References
Correction to: Evaluating the Effects of Chaos in Variable Neighbourhood Search
Correction to: Chapter "Evaluating the Effects of Chaos in Variable Neighbourhood Search" in: L. Di Gaspero et al. (Eds.): Metaheuristics, LNCS 13838, https://doi.org/10.1007/978-3-031-26504-4_15
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