Heuristic Search The Emerging Science of Problem Solving

• Main Author: Salhi, Saïd
• Format: eBook Publication
• Language: English
• Published: Cham Springer International Publishing 2017; Springer International Publishing AG; Palgrave Macmillan
• Edition: 1
• Series: SpringerLink
• Subjects: Algorithm Analysis and Problem Complexity; Algorithms; Big data; Big Data/Analytics; Business; Business and Management; Business Information Systems; Computer science; Computer Science, general; Computer software; Decision making; Heuristic; Heuristik; Management information systems; Operations research; Operations Research/Decision Theory; Problem solving; Theorie

This book aims to provide a general overview of heuristic search, to present the basic steps of the most popular heuristics, and to stress their hidden difficulties as well as their opportunities. It provides a comprehensive understanding of Heuristic search, the applications of which are now widely...

Table of Contents:

• A Simple Example of a Basic SA Implementation -- SA Key Elements -- Initial Value of the Temperature -- The Final Temperature Tf -- The Updating of the Temperature -- Flexibility in Resetting the Temperature -- The Evaluation Function Speed Ups -- Stopping Criteria -- Some Thoughts -- 3.2 TA Heuristics -- Algorithm 3.2: A Basic TA Heuristic -- Record to Record Heuristic -- List-Based TA -- Some Thoughts -- 3.3 Tabu Search (TS) -- Basic Terminology -- The TS Algorithm -- Algorithm 3.3: A Basic TS Heuristic -- Basic Explanations of the Steps -- TS Key Elements -- Tabu Restrictions -- Tabu List Size |Ts| -- Constant |Ts| -- Dynamic Changes in |Ts| -- Soft Aspiration Level -- Softer Aspiration Level -- Diversification and Intensification -- Strategic Oscillation (SO) -- Some Thoughts -- 3.4 Summary -- References -- 4: Population-Based Heuristics -- 4.1 Genetic Algorithms -- Algorithm 4.1: A Basic Genetic Algorithm -- Chromosome Representation -- Integer/Real Numbers Representation -- GA Operators -- Bit Mutation -- Inversion -- Crossover Operators -- One Point Crossover -- Multi Points Crossover -- PMX Operator -- Reproduction/Selection Mechanisms -- Tournament Selection -- Matching Issues -- Flexible Reproduction -- Effect of Migration -- Fitness Function Representation -- Some Thoughts -- 4.2 Scatter Search -- Algorithm 4.2: A Basic Scatter Search Heuristic -- Some Thoughts -- 4.3 Harmony Search -- Illustrative Example -- Algorithm 4.3: Basic Harmony Search Heuristic -- Discrete Case -- Some Thoughts -- 4.4 Differential Evolution -- Algorithm 4.4: A Basic Differential Evolution Heuristic -- Some Thoughts -- 4.5 Ant Colonies -- Introduction to Ant System -- Selection Rule -- Local Updating -- Global Updating -- The AS Algorithm -- Algorithm 4.5: A Basic AS Heuristic -- Ant Colony System -- Modified Transition Rule -- Local Updating -- Other Variants
• Intro -- Preface -- Acknowledgements -- Contents -- List of Algorithms -- List of Figures -- List of Table -- 1: Introduction -- 1.1 Introduction -- 1.2 The Optimisation Problem -- Local versus Global Optimality -- Local Search -- 1.3 Possible Methodological Approaches -- Algorithm 1.1: A Possible Recursive Methodological Approach -- 1.4 Need for Heuristics -- 1.5 Some Characteristics of Heuristics -- 1.6 Complexity and Performance of Heuristics -- Solution Quality -- Computational Effort -- Time Complexity -- Space Complexity -- `Real´ Meaning of Large or Small Computing Time -- 1.7 A Possible Heuristic Classification -- 1.8 Summary -- References -- 2: Improvement-Only Heuristics -- 2.1 Neighbourhood Definition and Examples -- The Travelling Salesman Problem -- The p-Median Problem -- The Bin Packing Problem -- The Vehicle Routing Problem -- Non-linear Optimisation Problems -- 2.2 Basic Descent or Hill Climbing Method -- Algorithm 2.1: The Basic Descent Method -- Initial Solutions (Step 1) -- Construction-Based Heuristics for the TSP -- Basic Enhancement of Step 1 in BDM -- Improvement Phase of the BDM (Step 2) -- Selection Strategies -- 2.3 Classical Multi-Start -- 2.4 GRASP -- Algorithm 2.2: A Basic GRASP -- Some Thoughts -- 2.5 Simple Composite Heuristics -- Algorithm 2.3: A Basic Composite Heuristic -- 2.6 A Multi-Level Composite Heuristic -- Algorithm 2.4: A Basic Multi-level Heuristic -- Some Thoughts -- 2.7 Variable Neighbourhood Search -- Algorithm 2.5: A Basic VNS Heuristic -- Some Thoughts -- 2.8 Problem Perturbation Heuristics -- Related Approaches -- Some Thoughts -- 2.9 Other Improving Only Methods -- Large Neighbourhood Search -- Iterated Local Search -- Guided Local Search -- 2.10 Summary -- References -- 3: Not Necessary Improving Heuristics -- 3.1 Simulated Annealing -- The Physical Analogy -- Algorithm 3.1: A Basic SA Heuristic
• A Simple Implementation and Adaptation -- 6.5 Parameters Estimation/Adaptive Search -- 6.6 Constraint Handling via SO -- 6.7 Impact of Parallelisation -- Master-Slaves Model -- Speed of Parallel Processing -- Internal Parallel Processing -- Effect of GPU -- 6.8 Fuzzy Logic -- 6.9 Dealing with Multiple Objectives -- 6.10 Summary -- References -- 7: Applications, Conclusion and Research Challenges -- 7.1 Real-Life Applications -- Radiotherapy -- Sport Management -- Manpower Scheduling -- Computational Chemistry -- Distribution Management (Routing) -- Location Issues -- Financial Portfolio Management -- Civil Engineering -- Chemical Engineering -- Other Engineering Applications -- General/Academic Type Applications -- 7.2 Conclusion -- 7.3 Research Challenges -- References -- Index
• Some Thoughts -- 4.6 The Bees Algorithm -- Algorithm 4.6: A Basic Bees Algorithm -- Algorithm 4.7: The ABC Algorithm -- Some Thoughts -- 4.7 Particle Swarm Optimisation -- Algorithm 4.8: A Basic PSO Heuristic -- Some Thoughts -- 4.8 A Brief on Other Population-Based Approaches -- Path Relinking -- CE-Based Algorithms -- Artificial Immune Systems -- The Plant Propagation Algorithm -- Psycho-Clonal Algorithm -- 4.9 Summary -- References -- 5: Hybridisation Search -- 5.1 Hybridisation of Heuristics with Heuristics -- Hyper-Heuristics -- Constructive Hyper-Heuristics -- A Brute Force Approach -- A Random Scheme -- A Learning-Based Approach -- Improvement Metaheuristics -- MA and Its Variants -- A Brief on Other Metaheuristic Hybridisations -- 5.2 Integrating Heuristics Within Exact Methods -- Injection of UB -- Tightening of LB and UB -- Lagrangean Relaxation Heuristics (LRH) -- Illustrative Example -- Reduction/Relaxation-Based Schemes -- Kernel Search -- Regular Seeking of New UBs -- Local Branching -- 5.3 Integration of ILP Within Heuristics/Metaheuristics -- Problem Decomposition -- Heuristic Concentration (HC) -- Multi-level Decomposition -- 5.4 Data Mining Hybridisation Search -- 5.5 Summary -- References -- 6: Implementation Issues -- 6.1 Data Structure -- Avoidance of the Recomputation of Already Computed Information -- Elimination of Common Tasks Which Are Used in Several Parts of the Method -- Avoidance of Extra Computation -- Tree-Based DS -- 6.2 Duplication Identification -- Hashing Function -- Simultaneous Use of Multiple Simple Performance Functions -- String-Based Checks -- Set-Based Identifications -- 6.3 Approximation Effect on Cost Function Evaluation -- 6.4 Reduction Tests/Neighbourhood Reduction -- Proximity-Based Scheme (Rule 1) -- Relaxing Flag(i,j) Due to Depot Location (Rule 2) -- Angle-Based Scheme (Rule 3)