Algorithms for nonlinear programming and multiple-objective decisions
著者
書誌事項
Algorithms for nonlinear programming and multiple-objective decisions
（Wiley-Interscience series in systems and optimization）
Wiley, c1998
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Algorithms for nonlinear programming and multiple objective decisions
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内容説明・目次
内容説明
Algorithms (solution methods) are used for optimal decision making with multiple objectives in operations research, management science, economics, finance and engineering design. An optimal decision needs to take into consideration possible future uncertainties which, as they become known, result in a necessary revision of the decision and the consideration of new future uncertainties. This volume is study of this topic. It is a distillation of research in developing methodologies and reflects research in this area. The question of multiple objective decision making with a nonlinear static problem framework is considered using quadratic programming, nonlinear programming, nonlinear constrained min-max, mean-variance optimization and noncooperative Nash games.
目次
- Optimization of a single objective
- quadratic programming algorithms
- interactive search for acceptable decisions - updating quadratic objective weights, updating bliss points and arbitrariness of shadow prices, convergence and complexity of decision processes
- nonlinear optimization with convex constraints - the Goldstein-Levitin-Polyak algorithm
- nonlinear optimization with equality and inequality constraints
- convergence rates of SQP algorithms
- algorithms for equilibria and games
- uncertainty
- mean versus variance optimization - the multi-currency portfolio
- the nonlinear case
- uncertainty with multiple scenarios - discrete min-max algorithm for equality constraints.
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