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 history, fundamental definitions, and underlying philosophies, and then detail the goal programming variants and define them algebraically. Chapter 3 details the step-by-step formulation of the basic goal programming model, and Chapter 4 explores more advanced modeling issues and highlights some recently proposed extensions. Chapter 5 then details the solution methodologies of goal programming, concentrating on computerized solution by the Excel Solver and LINGO packages for each of the three main variants, and includes a discussion of the viability of the use of specialized goal programming packages. Chapter 6 discusses the linkages between Pareto Efficiency and goal programming. Chapters 3 to 6 are supported by a set of ten exercises, and an Excel spreadsheet giving the basic solution of each example is available at an accompanying website. Chapter 7 details the current state of the art in terms of the integration of goal programming with other techniques, and the text concludes with two case studies which were chosen to demonstrate the application of goal programming in practice and to illustrate the principles developed in Chapters 1 to 7. Chapter 8 details an application in healthcare, and Chapter 9 describes applications in portfolio selection.

This volumecomprisesthe proceedingsof the 8th InternationalConferenceon M- tiple Objective and Goal Programming: Theories and Applications (MOPGP08). ThisconferencewasheldinPortsmouth, UnitedKingdomonthe24th-26thSept- ber 2008. The conference was attended by 59 delegates. The countries represented were Belgium, Finland, France, Germany, Italy, Kuwait, Poland, Saudi Arabia, South Africa, Spain, Switzerland, United Kingdom, and United States. The MOPGP conference series is now a well-established discussion forum for practitioners and academics working in the eld of multiple objective and goal p- gramming. Conferences are held every 2 years, with previous conferences taking place in Portsmouth, UK in 1994;in Malaga, Spainin 1996;in QuebecCity, Canada in 1998; in Ustron, Poland in 2000; in Nara, Japan in 2002; in Hammamet, Tunisia in 2004; and in Tours, France in 2006. The selection of papers published in this volume re ects the breadth of the techniques and applications in the eld of multiple objective and goal progr- ming. Applications from the elds of supply chain management, nancial portfolio selection, nancial risk management, insurance, medical imaging, sustainability, nurse scheduling, project management, and the interface with data envelopment analysis give a good re ection of current usage. A pleasing variety of techniques are used, including models with fuzzy, group-decision, stochastic, interactive, and binary aspects. Additionally, two papers from the upcoming area of multi-objective evolutionary algorithms are included. As organisersof the MOGP08 conference, we thank all the participants and p- senters at the conference for helping the MOPGP series to continue to de ne and develop the state-of-the-artin the eld of multiple objective and goal programmi

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 history, fundamental definitions, and underlying philosophies, and then detail the goal programming variants and define them algebraically. Chapter 3 details the step-by-step formulation of the basic goal programming model, and Chapter 4 explores more advanced modeling issues and highlights some recently proposed extensions.

Chapter 5 then details the solution methodologies of goal programming, concentrating on computerized solution by the Excel Solver and LINGO packages for each of the three main variants, and includes a discussion of the viability of the use of specialized goal programming packages. Chapter 6 discusses the linkages between Pareto Efficiency and goal programming. Chapters 3 to 6 are supported by a set of ten exercises, and an Excel spreadsheet giving the basic solution of each example is available at an accompanying website.

Chapter 7 details the current state of the art in terms of the integration of goal programming with other techniques, and the text concludes with two case studies which were chosen to demonstrate the application of goal programming in practice and to illustrate the principles developed in Chapters 1 to 7. Chapter 8 details an application in healthcare, and Chapter 9 describes applications in portfolio selection.

Most real-life problems involve making decisions to optimally achieve a number of criteria while satisfying some hard or soft constraints. In this book several methods for solving such problems are presented by the leading experts in the area. The book also contains a number of very interesting application papers which demonstrate theoretical modelling, analysing and solution of real-life problems.