Abstract
Increasingly, consumer demand of fashionable products is arising as significant challenge for company managers. In order to respond to this demand, companies are asked to supply small series of innovative and fashionable goods of high quality, affordable price and eco-compatibility in short periods of time and with high service levels. As a result of these rapidly evolving challenges, companies are forming collaborative networks in order to design, develop, produce and distribute such products and services in a collaboratively way. These highly integrated and dynamic supply networks depend intensively in new set of tools, methods and related services in which rely the collaborative networking operation. This paper presents a specific case study implementation of these collaborative supporting services, through the realization of a collaborative portal.

Abstract
Driven by a real-world application in the capital-intensive glass container industry, this paper provides the design of a new hybrid evolutionary algorithm to tackle the short-term production planning and scheduling problem. The challenge consists of sizing and scheduling the lots in the most cost-effective manner on a set of parallel molding machines that are fed by a furnace that melts the glass. The solution procedure combines a multi-population hierarchically structured genetic algorithm (GA) with a simulated annealing (SA), and a tailor-made heuristic named cavity heuristic (CH). The SA is applied to intensify the search for solutions in the neighborhood of the best individuals found by the GA, while the CH determines quickly values for a relevant decision variable of the problem: the processing speed of each machine. The results indicate the superior performance of the proposed approach against a state-of-the-art commercial solver, and compared to a non-hybridized multi-population GA.

Abstract
In food supply chain planning, the trade-off between expected profit and risk is emphasized by the perishable nature of the goods that it has to handle. In particular, the risk of spoilage and the risk of revenue loss are substantial when stochastic parameters related to the demand, the consumer behavior, and the spoilage effect are considered. This paper aims to expose and handle this trade-off by developing risk-averse production planning models that incorporate financial risk measures. In particular, the performance of a risk-neutral attitude is compared to the performance of models taking into account the upper partial mean and the conditional value-at-risk. Insights from an illustrative example show the positive impact of the-risk-averse models in operational performance indicators, such as the amount of expired products. Furthermore, through an extensive computational experiment, the advantage of the conditional value-at-risk model is evidenced, as it is able to dominate the solutions from the upper partial mean for the spoilage performance indicator. These advantages are tightly related to a sustainable view of production planning, and they can be achieved at the expense of controlled losses in the expected profit.

Abstract
Mathematical formulations for production planning are increasing complexity, in order to improve their realism. In short-term planning, the desirable level of detail is particularly high. Exact solvers fail to generate good quality solutions for those complex models on medium- and large-sized instances within feasible time. Motivated by a real-world case study in the pulp and paper industry, this paper provides an efficient solution method to tackle the short-term production planning and scheduling in an integrated mill. Decisions on the paper machine setup pattern and on the production rate of the pulp digester (which is constrained to a maximum variation) complicate the problem. The approach is built on top of a mixed integer programming (MIP) formulation derived from the multi-stage general lotsizing and scheduling problem. It combines a Variable Neighbourhood Search procedure which manages the setup-related variables, a specific heuristic to determine the digester's production speeds and an exact method to optimize the production and flow movement decisions. Different strategies are explored to speed-up the solution procedure and alternative variants of the algorithm are tested on instances based on real data from the case study. The algorithm is benchmarked against exact procedures.

Abstract
This paper is addressed to the generalization of simple plant location problem where customer's preferences are taken into account. Some basic polyhedral studies and a new family of facet-defining inequalities are given. The effectiveness of the proposed approach is illustrated by the computational experience.

Abstract
As a combination of different methodologies or parts of methodologies, Multimethodology is becoming more frequent in OR practice. This paper contributes with a new proposal and a new field of application: the employment of Multimethodology in problem solving with Metaheuristics (Mh). A convenient selection of soft and hard methods will be considered, from Soft OR, Creativity and Metaheuristics, such as Strategic Choice Approach, SWOT Analysis and Divergent and Convergent thinking. Formulating the 'right' optimisation problem, choosing a method based on Mh and accomplishing an effective implementation is an imprecise decision-making process, which may require skills and ideas that are beyond the ordinary boundaries of Mh practice. The relevance and success of Mh have been well-known for decades, but some open questions concerning choice and implementation strategies, for instance, still remain. If these questions are not adequately answered, they may lose credibility in the long term. The quality of solutions and computational times are not the only criteria used to analyse Mh, nor are they the most important. Very often, the effectiveness of an approach has to be evaluated from the perspective of modelling and practical problem solving. This paper investigates the advantages of Multimethodology and, furthermore, it sketches a framework for a coherent and comprehensive comparison of Mh and recommends a dynamic guiding tool for their implementation.