This book, developed through class instruction at MIT over the last 15 years, provides an accessible, concise, and intuitive presentation of algorithms for solving convex optimization problems. It relies on rigorous mathematical analysis, but also aims at an intuitive exposition that makes use of vi
A branch-and-bound algorithm for multiobjective mixed-integer convex optimization
โ Scribed by Rocktaschel S
- Publisher
- Springer
- Year
- 2020
- Tongue
- English
- Leaves
- 72
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Table of Contents
Contents......Page 7
1 Introduction......Page 9
2.1 Basics of multiobjective optimization......Page 12
2.2 The central multiobjective mixed-integeroptimization problem......Page 16
2.3 A relaxation of (MOMICP)......Page 22
3 A basic Branch-and-Boundalgorithm for (MOMICP)......Page 23
3.1 The selection rule......Page 25
3.2 The bisection step......Page 27
3.3 A necessary feasibility condition......Page 30
3.4 Determining lower bounds......Page 33
3.5 Determining upper bounds......Page 36
3.6 The discarding test and termination rule......Page 40
4.1 Preinitialization......Page 46
4.2 Elimination step......Page 50
4.3 Decrease box width......Page 51
4.4 Enhanced algorithm and theoretical results......Page 52
5 Test instances and numericalresults......Page 55
6 Outlook and further possibleimprovements......Page 64
7 Conclusion......Page 66
Bibliography......Page 67
Plots referring to the numericaltests......Page 69
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