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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2005.10.017 Byline: Rafael Caballero (a), Mercedes Gonzalez (a), Flor Ma Guerrero (b), Julian Molina (a), Concepcion Paralera (b) Keywords: Location routing problems; Multiobjective combinatorial optimization; Metaheuristics Abstract: In this work we present a multiobjective location routing problem and solve it with a multiobjective metaheuristic procedure. In this type of problem, we have to locate some plants within a set of possible locations to meet the demands of a number of clients with multiple objectives. This type of model is used to solve a problem with real data in the region of Andalusia (Spain). Thus, we study the location of two incineration plants for the disposal of solid animal waste from some preestablished locations in Andalusia, and design the routes to serve the different slaughterhouses in this region. This must be done while taking into account certain economic objectives (start-up, maintenance, and transport costs) and social objectives (social rejection by towns on the truck routes, maximum risk as an equity criterion, and the negative implications for towns close to the plant). Author Affiliation: (a) Faculty of Economics, Department of Applied Economics (Mathematics), University of Malaga, Campus El Ejido, 29007 Malaga, Spain (b) Department of Economy and Business, University Pablo de Olavide, Ctra. de Utrera, Km. 1- 41013 Sevilla, Spain

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2005.04.040 Byline: Rafael Caballero (a), Francisco Ruiz (a), M. Victoria Rodriguez Uria (b), Carlos Romero (c) Keywords: Goal programming; Meta-goal programming; Interactive; Satisficing Abstract: The concept of meta-goal programming is developed and linked to an interactive framework. An algorithm is proposed, in which the decision maker can establish target values on several achievement functions and use an interactive procedure to update these values. This substantially alleviates the problems associated with assigning to each attribute a target value, in order to build the goals, as well as the selection of a suitable achievement function. The functioning of the proposed interactive approach is illustrated with the help of an example taken from the farm management literature. Author Affiliation: (a) Departamento de Economia Aplicada (Matematicas), Facultad de Ciencias Economicas y Empresariales, Universidad de Malaga, Campus El Ejido s/n, 29071 Malaga, Spain (b) Departamento de Economia Cuantitativa, Facultad de Ciencias Economicas y Empresanales, Universidad de Oviedo, Campus del Cristo, 33006 Oviedo, Spain (c) Departamento de Economia y Gestion Forestal, ETS Ingeniero de Montes Universidad Politecnica de Madrid, Avda, Complutense s/n 28040 Madrid, Spain Article History: Received 8 June 2004; Accepted 26 April 2005

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2004.08.042 Byline: Rafael Caballero, Monica Hernandez Keywords: Goal programming; Fractional programming; Restoration of efficiency Abstract: The problem resulting from a goal programming problem with linear fractional criteria is not easy to solve due to the non-linear constraints inherent in its formulation. This paper introduces a simple and reliable test to establish whether a linear fractional goal programming problem has solutions that verify all goals and, if so, how to find them by solving a linear programming problem. This paper also outlines a new technique for restoring efficiency based on a minimax philosophy. An example is presented. Author Affiliation: Department of Applied Economics (Mathematics), University of Malaga, Campus El Ejido s/n, 29071 Malaga, Spain Article History: Received 4 February 2003; Accepted 30 August 2004

The problem of achieving efficient solutions in stochastic multiobjective programming by combining the techniques of both stochastic and multiobjective approaches, in a double transformation of the problem, is investigated. It is identified from the investigation that the order of transformation followed may have its impact on the efficiency of the solutions provided.

Goal Programming is considered with regard to GP variants in decision making, and the Meta-GP approach is examined.

The weakness of Goal Programming algorithms in producing dominated solutions have been improved by the use of an interactive algorithm that uses the decision maker's input of priority levels. The interactive algorithm allows for the recycling of generated values of the objective functions, with each recycling generating a Pareto optimal evaluation measure which in the end is evaluated for a single value, representing the optimal solution to the problem.