The aim of this volume is to show how Fuzzy Sets and Systems can help to provide robust and adaptive heuristic optimization algorithms in a variety of situations. The book presents the state of the art gives a broad overview on the real practical applications that Fuzzy Sets based heuristic algorithms have.

Inhalt

1. Soft Computing and Metaheuristics.- Fuzzy Adaptive Neighborhood Search: Examples of Application.- 1 Introduction.- 2 Description of FANS.- 3 On the Usefulness of Fuzzy Valuations.- 4 Examples of Application.- 5 Conclusions.- References.- Branch-and-bound algorithms using fuzzy heuristics for solving large-scale flow shop scheduling problems.- 1 Introduction.- 2 Lower bounds.- 3 Dominance rules and fuzzy approximation.- 4 Branch-and-bound algorithm.- 5 Computational experiments.- 6 Concluding remarks.- References.- A Fuzzy Adaptive Partition Algorithm (FAPA) for Global Optimization.- 1 Introduction.- 2 Fuzzy Adaptive Partitioning Approach.- 3 Computational Results.- 4 Conclusion.- References.- Fuzzy Memes in Multimeme Algorithms: a Fuzzy-Evolutionary Hybrid.- 1 Introduction.- 2 The Protein Structure Prediction Problem.- 3 Memetic Algorithms.- 4 Fuzzy Memes for Multimeme Algorithms.- 5 Experiments setup and results.- 6 Conclusions.- References.- Vehicle Routing Problem With Uncertain Demand at Nodes: The Bee System and Fuzzy Logic Approach.- 1 Introduction.- 2 Statement of the problem.- 3 A Proposed solution of the problem.- 4 Results obtained using the "intelligent" vehicle routing system.- 5 Conclusion.- References.- Fuzzy Constructive Heuristics.- 1 Introduction.- 2 Fuzzy Constructive Methods.- 3 Fuzzy Stopping Rules.- 4 The non-guillotine rectangular two-dimensional cutting problem.- 5 Computational experiments.- References.- 2. Heuristics and Mathematical Programming.- Heuristics for Optimization: two approaches for problem resolution.- 1 Introduction.- 2 Fuzzy rule learning in FMP.- 3 Fuzzy rule learning in MFGN framework.- 4 Analysis of results.- 5 Conclusions.- References.- Optimization with linguistic variables.- 1 Introduction.- 2 Optimization with linguistic variables.- 3 Examples.- 4 Extensions.- 5 Summary.- References.- Interactive Algorithms Using Fuzzy Concepts for Solving Mathematical Models of Real Life Optimization Problems.- 1 Introduction.- 2 Non-Symmetric Treatment of Linear and a Class of Non-Linear Multiobjective Fuzzy Programming Problems.- 3 PL-Pareto Optimal Solution.- 4 Calculation of Fuzzy Aspiration Levels.- 5 The Proposed IMMOFP Interactive Algorithm.- 6 Illustrative Examples.- 7 Concluding Observations.- References.- Fuzzy Data Envelopment Analysis: A Credibility Approach.- 1 Introduction.- 2 Fuzzy DEA Model.- 3 Possibility, Necessity, and Credibility Measures.- 4 CP-DEA model.- 5 Numerical Examples.- 6 Concluding Remarks.- References.- Fuzzy Optimization using Simulated Annealing: An Example Set.- 1 Introduction.- 2 Basics on the approach used for formulating and solving the example set.- 3 Set of linear examples tested and discussion of the results.- 4 Set of non-linear examples tested and discussion of the results.- 5 Conclusions.- References.- 3. Practical Heuristic Algorithms.- Multi-stage Supply Chain Network by Hybrid Genetic Algorithms.- 1 Introduction.- 2 Mathematical Model.- 3 Design of the Algorithm.- 4 Overall Procedure.- 5 Numerical Examples.- 6 Conclusion.- References.- Fuzzy evolutionary approach for multiobjective combinatorial optimization: application to scheduling problems.- 1 Introduction.- 2 Multiobjective Optimization: The State Of The Art.- 3 Fuzzy Evolutionary Approach.- 4 Application: Case Of Flexible Job-shop Scheduling Problem (FJSP).- 5 Discussions And Conclusions.- References.- Fuzzy Sets based Heuristics for Optimization: Multi-objective Evolutionary Fuzzy Modeling.- 1 Introducction.- 2 Fuzzy model identification.- 3 A technique to improve transparency and compactness of the fuzzy rule sets.- 4 Training of the RBF neural networks.- 5 Criteria for fuzzy modeling.- 6 Multi-objective neuro-evolutionary algorithm.- 7 Experiments and results.- 8 Conclusions and future research.- References.- An Interactive Fuzzy Satisficing Method for Multiobjective Operation Planning in District Heating and Cooling Plants through Genetic Algorithms for Nonlinear 0-1 Programming.- 1 Introduction.- 2 Operational Planning of a DHC Plant.- 3 An Interactive Fuzzy Satisficing Method.- 4 Genetic Algorithms for Nonlinear 0-1 Programming.- 5 Numerical Experiments.- 6 Conclusion.- References.- Adaptive Hybrid Genetic Algorithm with Fuzzy Logic Controller.- 1 Introduction.- 2 Adaptive Genetic Operators (AGOs).- 3 Proposed Hybrid Concepts and Logics.- 4 Proposed Algorithms for Experimental Comparison.- 5 Numerical Example.- 6 Conclusion.- References.- 4. Applications to Real World Problems.- Finding Satisfactory Near-Optimal Solutions in Location Problems.- 1 Introduction.- 2 The fuzzy p-median problem.- 3 Calculating the satisfaction level.- 4 An interchange heuristic procedure.- 5 Computational results.- 6 Conclusions.- References.- Route Choice Making Under Uncertainty: a Fuzzy Logic Based Approach.- 1 Introduction.- 2 Modeling Traffic Assignment.- 3 Fuzzy Sets as a Basis for Representing Imperfections.- 4 Fuzzy Sets Based Heuristics for Traffic Assignment.- 5 Analysis of the Model.- 6 Conclusions and Perspectives.- References.- A New Technique to Electrical Distribution System Load Flow Based on Fuzzy Sets.- 1 Introduction.- 2 Fuzzy Number.- 3 Fuzzy Numbers' Operators.- 4 Fuzzy Load Flow.- 5 Tests.- 6 Conclusions.- References.- A Fuzzy Adaptive Partitioning Algorithm (FAPA) for Global Optimization: Implementation in Environmental Site Characterization.- 1 Introduction.- 2 Environmental Site Characterization: Problem Definition.- 3 Implementation of Fuzzy Adaptive Partitioning Algorithm (FAPA) in Site Characterization.- 4 Numerical Results on Hypothetical Sites.- 5 Conclusion.- References.- Capacitated Vehicle Routing Problem with Fuzzy Demand.- 1 Introduction.- 2 A Fuzzy Multi-Criteria Modeling Approach.- 3 A Fuzzy Multi-Criteria Savings Heuristic.- 4 Conclusion.- References.- An Adaptive, Intelligent Control System for Slag Foaming.- 1 Introduction.- 2 The Problem Environment: Slag Foaming in an Electric Arc Steel Furnace.- 3 An Architecture for Achieving Intelligent Adaptive Control.- 4 Results.- 5 Summary.- References.