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New Developments in Multiple Objective and Goal Programming / edited by Dylan Jones, Mehrdad Tamiz, Jana Ries
Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: SpringerLink Bücher | Lecture notes in economics and mathematical systems ; 638Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010Description: Online-Ressource (X, 163 p. 23 illus, online resource)ISBN:- 9783642103544
- Multikriterielle Entscheidungsanalyse
- Theorie
- Mehrkriterielle Optimierung
- Zielprogrammierung
- Mathematics
- Production management
- Decision making
- Computer mathematics
- Mathematical models
- Management science
- Economics
- Artificial intelligence
- Mathematical optimization
- Operations research
- Business logistics
- Programming (Mathematics) Congresses
- Multiple criteria decision making Congresses
- 518
- 519.7
- QA71-90
- HD30.23
Contents:
Summary: Multi-Objective Stochastic Programming Approaches for Supply Chain Management -- A Review of Goal Programming for Portfolio Selection -- A Hypervolume-Based Optimizer for High-Dimensional Objective Spaces -- Minimizing Vector Risk Measures -- Multicriteria Programming Approach to Development Project Design with an Output Goal and a Sustainability Goal -- Automated Aggregation and Omission of Objectives for Tackling Many-Objective Problems -- Trade-Off Analysis in Discrete Decision Making Problems Under Risk -- Interactive Multiobjective Optimization for 3D HDR Brachytherapy Applying IND-NIMBUS -- Multicriteria Ranking Using Weights Which Minimize the Score Range -- In Search of a European Paper Industry Ranking in Terms of Sustainability by Using Binary Goal Programming -- Nurse Scheduling by Fuzzy Goal Programming.Summary: This volume shows the state-of-the-art in both theoretical development and application of multiple objective and goal programming. Applications from the fields of supply chain management, financial portfolio selection, financial risk management, insurance, medical imaging, sustainability, nurse scheduling, project management, water resource management, and the interface with data envelopment analysis give a good reflection of current usage. A pleasing variety of techniques are used including models with fuzzy, group-decision, stochastic, interactive, and binary aspects. Additionally, two papers from the upcoming area of multi-objective evolutionary algorithms are included. The book is based on the papers of the 8th International Conference on Multi-Objective and Goal Programming (MOPGP08) which was held in Portsmouth, UK, in September 2008.PPN: PPN: 164998104XPackage identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS | ZDB-2-SBE
New Developments in Multiple Objective and Goal Programming; Multi-Objective Stochastic Programming Approaches for Supply Chain Management; 1 Introduction; 2 Problem Description; 3 Multi-Objective Techniques; 3.1 Goal Attainment Technique; 3.2 STEM Method; 3.3 Surrogate Worth Trade-Off (SWT) Method; 4 Numerical Experiments; 5 Conclusion; References; A Review of Goal Programming for Portfolio Selection; 1 Introduction; 2 The Use of Multi-Criteria Decision Analysis in Portfolio Selection and the Importance of Goal Programming
3 Portfolio Selection Using Goal Programming: Theoretical and Practical Developments4 Goal Programming Variants for Portfolio Selection; 4.1 Weighted Goal Programming in Portfolio Selection Models; 4.2 Lexicographic Goal Programming in Portfolio Selection Models; 4.3 MINMAX (Chebyshev) Goal Programming in Portfolio Selection Models; 4.4 Fuzzy Goal Programming in Portfolio Selection Models; 5 Performance Measurement for Portfolios; 6 Goal Programming and Portfolio Analysis: Other Issues; 6.1 Issues Concerning Multi-Period Returns; 6.2 Issues Concerning Extended Factors
6.3 Issues Concerning the Measurement of Risk7 Conclusions; References; A Hypervolume-Based Optimizer for High-Dimensional Objective Spaces; 1 Motivation; 2 Related Work; 3 HypE: Hypervolume Estimation Algorithm for Multiobjective Optimization; 3.1 Algorithm; 3.2 Basic Scheme for Mating Selection; 3.3 Extended Scheme for Environmental Selection; 3.4 Estimating the Fitness Values Using Monte Carlo Sampling; 4 Experiments; 4.1 Experimental Setup; 4.2 Results; 5 Conclusion; References; Minimizing Vector Risk Measures; 1 Introduction; 2 Dealing with Vector Risk Functions
3 Saddle Point Optimality Conditions4 Applications; 4.1 Portfolio Choice; 4.2 Optimal Reinsurance; 5 Conclusions; References; Multicriteria Programming Approach to Development Project Design with an Output Goal and a Sustainability Goal; 1 Introduction; 2 Methodology; 2.1 First Objective: Output Maximization; 2.2 Second Objective: Sustainability; 2.3 Compromise Solution; 2.4 Feedback; 3 An Illustrative Example; 3.1 First Objective: Output Maximization (Unrelatedto the Pattern); 3.2 Second Objective: Sustainability (Related to the Pattern)
3.3 Compromise Solution and Final Solution on the Frontier3.4 Comparison of Results; 4 Concluding Remarks; References; Automated Aggregation and Omission of Objectives for Tackling Many-Objective Problems; 1 Introduction; 2 Objective Reduction by Aggregating Objectives; 3 A Greedy Heuristic for Finding the Best Aggregation; 3.1 Main Procedure; 3.2 Optimally Aggregating Two Objectives; 4 Experimental Validation; 4.1 The Influence of Different Weight Choices Within the Optimal Interval; 4.2 Comparison Between Aggregation and Omission; 4.3 Objective Reduction During Search
5 Application to a Real-World Problem
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