## Handbook of critical issues in goal programmingGoal Programming (GP) is perhaps the oldest and most widely used approach within the Multiple Criteria Decision Making (MCDM) paradigm. GP combines the logic of optimisation in mathematical programming with the decision maker's desire to satisfy several goals. The primary purpose of this book is to identify the critical issues in GP and to demonstrate different procedures capable of avoiding or mitigating the inherent pitfalls associated with these issues. The outcome of a search of the literature shows many instances where GP models produced misleading or even erroneous results simply because of a careless formulation of the problem. Rather than being in itself a textbook, Critical Issues in Goal Programming is designed to complement existing textbooks. It will be useful to students and researchers with a basic knowledge of GP as well as to those interested in building GP models which analyse real decision problems. |

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### Contents

Chapter 2 | 13 |

Equivalence of Solutions between GP and LP Models | 26 |

An Introduction to the Problem | 50 |

Copyright | |

9 other sections not shown

### Common terms and phrases

achievement function Agricultural Economics algorithm alternative optimal solutions analysis chapter Charnes Computers and Operations constraint Cordoba University corresponding direct linearization efficient set efficient solutions Euclidean norm European Journal example feasible set formulation fractional goal goal programming approach goal programming model goals g2 GP model GP variant GP-efficient solutions Hannan ideal alternative Ignizio inferior solutions Journal of Operational Kornbluth Kvanli's lexicographic orderings LGP problem linear programming logarithmic transformation Management Science Mathematical Programming maximization MCDM approaches metric minimized MINMAX GP Multiple criteria decision multiple objective negative deviational variables nonefficient number of priority objective function Omega Operational Research Society Paretian efficiency Pareto Pareto optimal penalty functions positive deviational variable posynomial preferences priority levels procedure redundant goals Rehman represent Romero set of GP-efficient Simplex algorithm solution obtained solution provided solved Soyster Steuer structure target value total penalty two-sided goals utility function x e F XXIV Zanakis Zeleny