Abstract
In this work we present a tabu search metaheuristic method for solving the permutation flow shop scheduling problem with sequence dependent setup times and the objective of minimising total weighted tardiness. The problem is well known for its practical applications and for the difficulty in obtaining good solutions. The tabu search method proposed is based on the insertion neighbourhood, and is characterised by the selection and evaluation of a small subset of this neighbourhood at each iteration; this has consequences both on diversification and intensification of the search. We also propose a speed-up technique based on book keeping information of the current solution, used for the evaluation of its neighbours. © 2014 Inderscience Enterprises Ltd.

Abstract

Abstract
This paper presents two new solution approaches capable of finding optimal solutions for the thermal unit commitment problem in power generation planning. The approaches explore the concept of "matheuristics", a term usually used to refer to an optimization algorithm that hybridizes (meta)heuristics with mixed integer programming solvers, in order to speed up convergence to optimality for large scale instances. Two algorithms are proposed: "local branching", and an hybridization of particle swarm optimization with a mixed integer programming solver. From extensive computational tests on a broad set of benchmarks, the algorithms were found to be able to solve large instances. Optimal solutions were obtained for several well-known situations with dramatic reductions in CPU time for the larger cases, when compared to previously proposed exact methods.

Abstract
The kidney exchange problem (KEP) is an optimization problem arising in the framework of transplant programs that allow exchange of kidneys between two or more incompatible patient-donor pairs. In this paper an approach based on a new decomposition model and branch-and-price is proposed to solve large KEP instances. The optimization problem considers, hierarchically, the maximization of the number of transplants and the minimization of the size of exchange cycles. Computational comparison of different variants of branch-and-price for the standard and the proposed objective functions are presented. The results show the efficiency of the proposed approach for solving large instances.

Abstract

Abstract
Within collaborative networks, information sharing and knowledge creation are the main drives for value creation, wherever collaborative spaces (CS) has been used as the means to enable collaboration among the different social actors involved. Despite of technological availability, CS still a challenge in practice, mainly due to the lack of methods to support its development and to its tight coupling with the collaboration model adopted by the network. Thus, the main focus of this paper in on enhancing information sharing through the design of what we call agnostic collaborative spaces (ACS), supported by linked data approaches. Beyond this new perspective over CS, it is discussed a technological solution through which ACS are implemented.