Parallel Problem Solving from Nature – PPSN XV

Table of Contents

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   Book Overview
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   Chapter 1 A Comparative Study of Large-Scale Variants of CMA-ES
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   Chapter 2 Design of a Surrogate Model Assisted (1 + 1)-ES
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   Chapter 3 Generalized Self-adapting Particle Swarm Optimization Algorithm
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   Chapter 4 PSO-Based Search Rules for Aerial Swarms Against Unexplored Vector Fields via Genetic Programming
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   Chapter 5 Towards an Adaptive CMA-ES Configurator
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   Chapter 6 A Probabilistic Tree-Based Representation for Non-convex Minimum Cost Flow Problems
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   Chapter 7 Comparative Study of Different Memetic Algorithm Configurations for the Cyclic Bandwidth Sum Problem
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   Chapter 8 Efficient Recombination in the Lin-Kernighan-Helsgaun Traveling Salesman Heuristic
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    Chapter 9 Escherization with a Distance Function Focusing on the Similarity of Local Structure
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    Chapter 10 Evolutionary Search of Binary Orthogonal Arrays
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    Chapter 11 Heavy-Tailed Mutation Operators in Single-Objective Combinatorial Optimization
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    Chapter 12 Heuristics in Permutation GOMEA for Solving the Permutation Flowshop Scheduling Problem
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    Chapter 13 On the Performance of Baseline Evolutionary Algorithms on the Dynamic Knapsack Problem
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    Chapter 14 On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains
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    Chapter 15 EDDA-V2 – An Improvement of the Evolutionary Demes Despeciation Algorithm
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    Chapter 16 Extending Program Synthesis Grammars for Grammar-Guided Genetic Programming
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    Chapter 17 Filtering Outliers in One Step with Genetic Programming
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    Chapter 18 GOMGE: Gene-Pool Optimal Mixing on Grammatical Evolution
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    Chapter 19 Self-adaptive Crossover in Genetic Programming: The Case of the Tartarus Problem
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    Chapter 20 A Decomposition-Based Evolutionary Algorithm for Multi-modal Multi-objective Optimization
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    Chapter 21 A Double-Niched Evolutionary Algorithm and Its Behavior on Polygon-Based Problems
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    Chapter 22 Artificial Decision Maker Driven by PSO: An Approach for Testing Reference Point Based Interactive Methods
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    Chapter 23 A Simple Indicator Based Evolutionary Algorithm for Set-Based Minmax Robustness
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    Chapter 24 Extending the Speed-Constrained Multi-objective PSO (SMPSO) with Reference Point Based Preference Articulation
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    Chapter 25 Improving 1by1EA to Handle Various Shapes of Pareto Fronts
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    Chapter 26 New Initialisation Techniques for Multi-objective Local Search
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    Chapter 27 Towards a More General Many-objective Evolutionary Optimizer
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    Chapter 28 Towards Large-Scale Multiobjective Optimisation with a Hybrid Algorithm for Non-dominated Sorting
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    Chapter 29 Tree-Structured Decomposition and Adaptation in MOEA/D
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    Chapter 30 Use of Reference Point Sets in a Decomposition-Based Multi-Objective Evolutionary Algorithm
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    Chapter 31 Use of Two Reference Points in Hypervolume-Based Evolutionary Multiobjective Optimization Algorithms
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    Chapter 32 Introducing an Event-Based Architecture for Concurrent and Distributed Evolutionary Algorithms
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    Chapter 33 Analyzing Resilience to Computational Glitches in Island-Based Evolutionary Algorithms
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    Chapter 34 Spark Clustering Computing Platform Based Parallel Particle Swarm Optimizers for Computationally Expensive Global Optimization
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    Chapter 35 Weaving of Metaheuristics with Cooperative Parallelism
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    Chapter 36 Conditional Preference Learning for Personalized and Context-Aware Journey Planning
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    Chapter 37 Critical Fractile Optimization Method Using Truncated Halton Sequence with Application to SAW Filter Design
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    Chapter 38 Directed Locomotion for Modular Robots with Evolvable Morphologies
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    Chapter 39 Optimisation and Illumination of a Real-World Workforce Scheduling and Routing Application (WSRP) via Map-Elites
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    Chapter 40 Prototype Discovery Using Quality-Diversity
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    Chapter 41 Sparse Incomplete LU-Decomposition for Wave Farm Designs Under Realistic Conditions
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    Chapter 42 Understanding Climate-Vegetation Interactions in Global Rainforests Through a GP-Tree Analysis