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In a R&D department, several projects may have to be implemented simultaneously within a certain period of time by a limited number of human resources with diverse skills. This paper proposes an optimisation model for the allocation of multi-skilled human resources to R&D projects, considering individual workers as entities having different knowledge, experience and ability. The model focuses on three fundamental aspects of human resources: the different skill levels, the learning process and the social relationships existing in working teams. The resolution approach for the multi-objective problem consists of two steps: firstly, a set of non-dominated solutions is obtained by exploring the optimal Pareto frontier and secondly, based on further information, the ELECTRE III method is utilised to select the best compromise with regards to the considered objectives. The uncertainty associated to each solution is modelled by fuzzy numbers and used in establishing the threshold values of ELECTRE III, while the weights of the objectives are determined taking into account the influence that each objective has on the others

The problem of facility layout design is discussed, taking into account the uncertainty of production scenarios and the finite production capacity of the departments. The uncertain production demand is modelled by a fuzzy number, and constrained arithmetic operators are used in order to calculate the fuzzy material handling costs. By using a ranking criterion, the layout that represents the minimum fuzzy cost is selected. A flexible bay structure is adopted as a physical model of the system while an effective genetic algorithm is implemented to search for a near optimal solution in a fuzzy contest. Constraints on the aspect ratio of the departments are taken into account using a penalty function introduced into the fitness function of the genetic algorithm. The efficiency of the genetic algorithm proposed is tested in a deterministic context and the possibility of applying the fuzzy approach to a medium-large layout problem is explored

Abstract. It is well known that halons are ozone-depleting substances and their\ud release into the atmosphere has contributed in the last decades to the reduction in the\ud ozone layer. In consequence to the Montreal Protocol, an international agreement\ud designed to gradually eliminate the use of such substances, fire protection industry\ud researchers faced the challenge of finding effective solutions to replace halon extinguishers.\ud This research aims to provide a method to support the decision maker in\ud the selection of the most suitable extinguisher substance for a specific application.\ud According to such framework, a set of quantitative and qualitative criteria has\ud been established in the decision-making problem. Such criteria have been properly\ud regrouped in clusters in order to better evaluate their relative importance by means of\ud AHP method and the criteria have been used for scoring the alternatives. The choice\ud of an extinguisher substance rather than another has been subsequently carried out\ud by means of a fuzzy TOPSIS approach, which reflects the vagueness of qualitative\ud criteria