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Goal-Directed Program Transformation
IEEE Transactions on Software Engineering, 1976Program development often proceeds by transforming simple, clear programs into complex, involuted, but more efficient ones. This paper examines ways this process can be rendered more systematic. We show how analysis of program performance, partial evaluation of functions, and abstraction of recursive function definitions from recurring subgoals can be ...
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2010
Practical Goal Programming is intended to allow academics and practitioners to be able to build effective goal programming models, to detail the current state of the art, and to lay the foundation for its future development and continued application to new and varied fields. Suitable as both a text and reference, its nine chapters first provide a brief
Jones, Dylan, Tamiz, M.
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Practical Goal Programming is intended to allow academics and practitioners to be able to build effective goal programming models, to detail the current state of the art, and to lay the foundation for its future development and continued application to new and varied fields. Suitable as both a text and reference, its nine chapters first provide a brief
Jones, Dylan, Tamiz, M.
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2010
This chapter introduces the major goal programming variants. The purpose and underlying philosophy of each variant are given. The three major variants in terms of underlying distance metric (and hence philosophy) used are introduced first. These are lexicographic, weighted, and Chebyshev goal programming.
Dylan Jones, Mehrdad Tamiz
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This chapter introduces the major goal programming variants. The purpose and underlying philosophy of each variant are given. The three major variants in terms of underlying distance metric (and hence philosophy) used are introduced first. These are lexicographic, weighted, and Chebyshev goal programming.
Dylan Jones, Mehrdad Tamiz
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2019
Goal programming (GP) is one of the vital branches of multi-objective optimization, which thusly is a part of multi-criteria decision analysis (MCDA). Goal programming (GP) is one of the best optimization techniques. It may be very well thought of as an expansion of linear programming or nonlinear programming to deal with various, typically clashing ...
Sahidul Islam, Wasim Akram Mandal
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Goal programming (GP) is one of the vital branches of multi-objective optimization, which thusly is a part of multi-criteria decision analysis (MCDA). Goal programming (GP) is one of the best optimization techniques. It may be very well thought of as an expansion of linear programming or nonlinear programming to deal with various, typically clashing ...
Sahidul Islam, Wasim Akram Mandal
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Goal types in agent programming
Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems, 2006This paper discusses three types of declarative goals and motivates their integration in logic-based agent-oriented programming languages. These goal types are perform goals, achieve goals, and maintain goals. A goal type is considered as a specific agent attitude towards goals.
Dastani, M.M. +2 more
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1995
Goal programming (GP) is a very applied methodology. In the over 980 journal citations listed in Appendix B,666 or over 68 percent are applications, case studies or applied models. Indeed, the diversity of application in GP is now so great that just their listing will absorb this entire chapter.
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Goal programming (GP) is a very applied methodology. In the over 980 journal citations listed in Appendix B,666 or over 68 percent are applications, case studies or applied models. Indeed, the diversity of application in GP is now so great that just their listing will absorb this entire chapter.
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MultiObjective Programming and Goal Programming
2009This book gives the reader an insight into the state of the art in the field of multiobjective (linear, nonlinear and combinatorial) programming, goal programming and multiobjective metaheuristics. The 26 papers describe all relevant trends in this fields of research .
Barichard, Vincent +3 more
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1992
Suppose that a manager has identified a problem that can be formulated as a traditional linear programming problem with one added complication — the decision being modeled must be judged on the basis of more than one criterion. Now let Z1(x), Z2(x), ..., Zh(x), ..., Zk(x) model the criteria as linear objective functions, g(x) be a set of linear ...
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Suppose that a manager has identified a problem that can be formulated as a traditional linear programming problem with one added complication — the decision being modeled must be judged on the basis of more than one criterion. Now let Z1(x), Z2(x), ..., Zh(x), ..., Zk(x) model the criteria as linear objective functions, g(x) be a set of linear ...
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