Goal 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.
For post-graduate students following courses in management science, operational research and industrial engineering, as well as courses in agricultural economics, forestry, fisheries management and socio-economic planning which cover GP.
Table of Contents
Section headings: Preface. Acknowledgements. An Introductory Overview of Goal Programming (GP) and Some Related Multiple Criteria Decision Making (MCDM) Approaches. Paretian Efficiency in Goal Programming. Good and Poor Modelling Practices in Goal Programming. Naive Prioritization and Redundancy in LGP. Hidden Nonlinearities in Linear Goal Programming Models. Goal Programming with Penalty Functions. Relationship between Goal Programming (GP), Multiobjective Programming (MOP) and Compromise Programming (CP). GP Applications: A Categorized Bibliographical Survey. Epilogue. Index.