Jones / Tamiz / Ries New Developments in Multiple Objective and Goal Programming

1. Auflage 2010
ISBN: 978-3-642-10354-4
Verlag: Springer
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 163 Seiten

Autoren/Hrsg.

Jones, Dylan

Tamiz, Mehrdad

Ries, Jana

Inhaltsverzeichnis

1;Preface;5
2;Contents;7
3;List of Contributors;9
4;Multi-Objective Stochastic Programming Approaches for Supply Chain Management;11
4.1;1 Introduction;11
4.2;2 Problem Description;13
4.3;3 Multi-Objective Techniques;15
4.3.1;3.1 Goal Attainment Technique;16
4.3.2;3.2 STEM Method;17
4.3.3;3.3 Surrogate Worth Trade-Off (SWT) Method;19
4.4;4 Numerical Experiments;20
4.5;5 Conclusion;23
4.6;References;23
5;A Review of Goal Programming for Portfolio Selection;25
5.1;1 Introduction;25
5.2;2 The Use of Multi-Criteria Decision Analysis in Portfolio Selection and the Importance of Goal Programming;26
5.3;3 Portfolio Selection Using Goal Programming: Theoretical and Practical Developments;29
5.4;4 Goal Programming Variants for Portfolio Selection;32
5.4.1;4.1 Weighted Goal Programming in Portfolio Selection Models;32
5.4.2;4.2 Lexicographic Goal Programming in Portfolio Selection Models;32
5.4.3;4.3 MINMAX (Chebyshev) Goal Programming in Portfolio Selection Models;33
5.4.4;4.4 Fuzzy Goal Programming in Portfolio Selection Models;33
5.5;5 Performance Measurement for Portfolios;35
5.6;6 Goal Programming and Portfolio Analysis: Other Issues;35
5.6.1;6.1 Issues Concerning Multi-Period Returns;36
5.6.2;6.2 Issues Concerning Extended Factors;37
5.6.3;6.3 Issues Concerning the Measurement of Risk;38
5.7;7 Conclusions;40
5.8;References;40
6;A Hypervolume-Based Optimizer for High-Dimensional Objective Spaces;44
6.1;1 Motivation;44
6.2;2 Related Work;46
6.3;3 HypE: Hypervolume Estimation Algorithm for Multiobjective Optimization;47
6.3.1;3.1 Algorithm;48
6.3.2;3.2 Basic Scheme for Mating Selection;49
6.3.3;3.3 Extended Scheme for Environmental Selection;51
6.3.4;3.4 Estimating the Fitness Values Using Monte Carlo Sampling;54
6.4;4 Experiments;55
6.4.1;4.1 Experimental Setup;55
6.4.2;4.2 Results;56
6.5;5 Conclusion;60
6.6;References;61
7;Minimizing Vector Risk Measures;64
7.1;1 Introduction;64
7.2;2 Dealing with Vector Risk Functions;66
7.3;3 Saddle Point Optimality Conditions;69
7.4;4 Applications;75
7.4.1;4.1 Portfolio Choice;75
7.4.2;4.2 Optimal Reinsurance;75
7.5;5 Conclusions;76
7.6;References;77
8;Multicriteria Programming Approach to Development Project Design with an Output Goal and a Sustainability Goal;79
8.1;1 Introduction;79
8.2;2 Methodology;80
8.2.1;2.1 First Objective: Output Maximization;81
8.2.2;2.2 Second Objective: Sustainability;82
8.2.3;2.3 Compromise Solution;82
8.2.4;2.4 Feedback;83
8.3;3 An Illustrative Example;83
8.3.1;3.1 First Objective: Output Maximization (Unrelatedto the Pattern);84
8.3.2;3.2 Second Objective: Sustainability (Related to the Pattern);84
8.3.3;3.3 Compromise Solution and Final Solution on the Frontier;85
8.3.4;3.4 Comparison of Results;86
8.4;4 Concluding Remarks;86
8.5;References;87
9;Automated Aggregation and Omission of Objectives for Tackling Many-Objective Problems;88
9.1;1 Introduction;88
9.2;2 Objective Reduction by Aggregating Objectives;89
9.3;3 A Greedy Heuristic for Finding the Best Aggregation;93
9.3.1;3.1 Main Procedure;93
9.3.2;3.2 Optimally Aggregating Two Objectives;93
9.4;4 Experimental Validation;97
9.4.1;4.1 The Influence of Different Weight Choices Within the Optimal Interval;98
9.4.2;4.2 Comparison Between Aggregation and Omission;99
9.4.3;4.3 Objective Reduction During Search;101
9.5;5 Application to a Real-World Problem;106
9.6;6 Conclusions;107
9.7;References;108
10;Trade-Off Analysis in Discrete Decision Making Problems Under Risk;110
10.1;1 Introduction;110
10.2;2 Formulation of the Problem;112
10.3;3 Point-to-Point Trade-Offs;113
10.4;4 The Procedure;115
10.5;5 Numerical Example;118
10.6;6 Conclusions;121
10.7;References;122
11;Interactive Multiobjective Optimization for 3D HDR Brachytherapy Applying IND-NIMBUS;123
11.1;1 Introduction;123
11.2;2 Methods;125
11.2.1;2.1 Dose Calculation;125
11.2.2;2.2 Objective Function Formulation;126
11.2.3;2.3 Multiobjective Optimization;127
11.2.3.1;2.3.1 Multiobjective Optimization Problem;127
11.2.3.2;2.3.2 The Interactive Multiobjective Optimization Method NIMBUS;128
11.3;3 Results;129
11.3.1;3.1 Problem Settings;129
11.3.2;3.2 Fletcher–Suit Applicator Example;130
11.3.2.1;3.2.1 Interactive Solution Process;130
11.3.2.2;3.2.2 Comparison and Discussion;133
11.4;4 Conclusions;135
11.5;References;136
12;Multicriteria Ranking Using Weights Which Minimizethe Score Range;138
12.1;1 Introduction;138
12.2;2 Geometric Representation;139
12.3;3 Can the Maximin Approach Produce a SingleWinning Alternative?;143
12.4;4 Criteria Can be Completely Ignored;143
12.5;5 Conclusion;143
12.6;References;144
13;In Search of a European Paper Industry Ranking in Terms of Sustainability by Using Binary Goal Programming;146
13.1;1 Introduction;146
13.2;2 Sustainability Indicators;147
13.3;3 Methodology;150
13.4;4 Results and Conclusions;152
13.5;References;153
14;Nurse Scheduling by Fuzzy Goal Programming;155
14.1;1 Introduction;155
14.2;2 Problem Statement: The Case Study;156
14.2.1;2.1 Legal and Policy Restrictions;157
14.2.2;2.2 Nurses' Preferences;157
14.3;3 Fuzzy Goal Programming;158
14.4;4 The Fuzzy Goal Programming Model for Scheduling Model;160
14.4.1;4.1 Hard Constraints;160
14.4.2;4.2 Fuzzy Goals;163
14.5;5 Results and Discussion;165
14.6;6 Concluding Remarks;166
14.7;References;167