The conical approach provides a geometrical understanding of optimization and is a powerful research tool and a useful problem solving technique (e.g., in decision support and real time control applications). Conical optimality conditions are first stated in a very general optimization framework and then applied to linear programming. A complete theory along with primal and dual algorithms are given, and solutions and algorithms are also provided for vector and robust linear optimization. The advantages of parameter dependence of conical methods are fully discussed. In addition to numerical results the book provides source code and detailed documentation of a Modula-2 implementation for the main algorithms.
The book can be used as a supplementary textbook for basic courses in linear programming or for more advanced courses in optimization. It is also a useful reference for researchers and professionals alike.
Presents conical optimization conditions in a general optimization framework and then applies them to linear programming. A complete theory is given, along with primal and dual algorithms, and solutions and algorithms are provided for vector and robust linear optimization. Discuses advantages of parameter dependence of conical methods, and provides source code and detailed documentation of a Modula-2 implementation for the main algorithms, in addition to numerical results. Can be used as a supplementary text for basic courses in linear programming or for more advanced courses in optimization. Annotation c. by Book News, Inc., Portland, Or.
The conical approach provides a geometrical understanding of optimization and is a powerful research tool and useful problem-solving technique (for example, in decision support and real time control applications).
Conical optimality conditions are first stated in a very general optimization framework, and then applied to linear programming. A complete theory along with primal and dual algorithms is given, and solutions and algorithms are also provided for vector and robust linear optimization. The advantages of parameter dependence of conical methods are fully discussed. In addition to numerical results, the book provides source codes and detailed documentation of a Modula-2 implementation for the main algorithms.
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