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.

Abstract

Abstract
In this paper, we present an integer linear programming model for the vehicle routing problem that considers real-world three-dimensional (3D) loading constraints. In this problem, a set of customers make requests of goods that are wrapped up in boxes, and the objective is to find minimum cost delivery routes for a set of identical vehicles that, departing from a depot, visit all customers only once and return to the depot. Apart from the usual 3D container loading constraints that ensure the boxes are packed completely inside the vehicles and the boxes do not overlap each other in each vehicle, the problem also takes into account constraints related to the vertical stability of the cargo, multidrop situations, and load-bearing strength of the boxes (including fragility). Computational tests with the proposed model were performed using an optimization solver embedded into a modeling language. The results validate the model and show that it is only able to handle problems of a moderate size. However, this model will be useful to motivate other researchers to explore approximate solution approaches to solve this problem, such as decomposition methods, relaxation methods, heuristics, among others, as well as to treat other variants of the problem, such as when time windows or a heterogeneous fleet are present, among others.

Abstract
The promotion of quality of life is becoming ever more important in a scenario of regional, national and even international competition among cities, triggered by globalization. Public sites, and green spaces in particular, which are available in varying extent in all urban areas, can bring important benefits to urban vitality and, as a consequence, to quality of life. However, cities are intricate entities and measuring their success in converting the potential for public green space usage into increased quality of life is a difficult task. In order to contribute to the objective of assessing the potential for public green space use, and its consequences on urban vitality, we applied the Data Envelopment Analysis technique to assess a total of 174 European cities. The results detect the best performing cities, and for the cities considered inefficient, a set of benchmarks is identified, whose best practices can be copied to support efforts of performance improvement.

Abstract
The use of optimization techniques is well established in forest short-term planning and decision-making. Yet, existing techniques may pose some limitations for tackling with stochastic factors impacting in the execution of forest operations, such as delays, equipment breakdowns and other unexpected events. This paper explores the potential of using optimization techniques in combination with discrete-event simulation (DES) models for planning harvesting and logistics operations acknowledging uncertainty. DES models may be useful for assessing the performance and identifying bottlenecks associated with the execution of the deterministic plans retrieved with optimization techniques, when such stochastic events occur. This paper further presents an approach for the combination of a heuristic and a DES model developed in SIMIO. This approach was used to solve the raw material reception problem (RMRP) at a Portuguese pulp mill. This paper concludes with the analysis of the performance of deterministic schedules for the wood trucks considering uncertainty in their arrival at the mill. © 2013 © 2013 Taylor & Francis.

Abstract
Joint production and distribution planning at the operational level has received a great deal of attention from researchers. In most industries these processes are decoupled by means of final goods inventory that allow for a separated planning of these tasks. However, for example, in the catering industry, an integrated planning framework tends to be more favorable due to the perishable nature of the products that forces a make-to-order production strategy. So far this planning problem has only been addressed by allowing the batching of orders. The main contribution of this paper is to extend this approach and prove the importance of lot sizing for make-to-order systems when perishability is explicitly considered. The value of considering lot sizing versus batching is further investigated per type of production scenario. Overall, results indicate that lot sizing is able to deliver better solutions than batching. On average, for the improved instances, the cost savings ascend to 6.5% when using lot sizing. The added flexibility of lot sizing allows for a reduction on production setup costs and both fixed and variable distribution costs. The savings derived from lot sizing are enhanced by customer oriented time windows and production systems with non-triangular setups.