Special issue on recent developments in multiple objective programming and goal programming

The fields of multiple objective programming and goal programming (MOP/GP) include areas in which methods and procedures are designed to solve problems within a mathematical programming framework and optimizing conflicting objectives. The application of MOP/GP procedures has contributed considerably to the improvement and competitiveness in many economic sectors and firms. Multiple objective programming poses several challenges ranging from model building to algorithmic design and implementation. The development of efficient tools has generated an increasing interest in the research and practitioner communities in recent years. Moreover, the evolution in hardware has played a fundamental role in solving real-world applications. This issue aims to compile some recent contributions in theoretical, methodological, and algorithmic developments, together with significant applications and case studies in the fields of MOP/GP. A series of international conferences devoted to these topics has motivated us to publish this issue. Most papers in this issue are taken from the presentations at the Ninth International Conference on Multiple Objective Programming and Goal Programming held in the city of Sousse, Tunisia from May 24 to 26, 2010. Other submissions were received following an open call for papers. The large number of submissions exceeded our initial expectations, showing the strong interest of the research community in these topics. Each submission was thoroughly reviewed and eight papers have been accepted for publication at the time we were closing this issue. Two other papers still under refereeing at this time will eventually be published in a regular issue of the journal. This special issue starts with a survey on the multiobjective multidimensional knapsack problem by T. Lust and J. Teghem. In the last part of their paper, the authors propose an adaptation of the two-phase Pareto local search to solve the multiobjective multidimensional knapsack problem. In the second paper, A. A. Foroughi and B. Aouni recognize that the definition of a common set of weights for a voting system is not a simple task, discussing some drawbacks of the existing models and proposing new approaches. D. Chaabane, B. Brahmi, and Z. Ramdani propose a new exact algorithm dedicated to multiobjective integer linear programming in the third paper. In the next paper, M. Gagnon, G. d’Avignon, and B. Aouni propose a multiobjective project scheduling approach. The concepts of goal programming and satisfaction function are used in order to get the