Abstract
Dizajn distributivne mreže predstavlja jednu od strateških odluka u konkurenciji za kompanije visokog uticaja. Optimalna lokacija objekata u odnosu na kapacitet ponude i potražnje omogucuje visokom nivou usluga prisustvo na tržištu. U ovom radu predstavljen je metodološki okvir za projektovanje distributivnih mreža kombinovanjem primene tehnika klastera i matematickog programiranja. Predložena metodologija je testirana sa realnim podacima dobijenim od kompanije bezalkoholnih pica u Kolumbiji. Pristup razmatra tri glavne faze. U prvoj fazi, proces klasteriranja kupaca vrši se pomocu K-sredstava kako bi se dobila lokacija za potencijalne distributivne centre (DC). U drugoj fazi, model za dizajn distributivne mreže se vrši pomocu mešovitog programiranja celih brojeva (MPCB) razmatrajuci razlicite opcije za dodeljivanje DC-ma. U finalnoj fazi vrši se procena predložene metodologije u realnom slucaju. Kao rezultat, definisana je distributivna šema koja omogucava ulaz u nova tržišna podrucja sa efikasnom strategijom za prodiranje proizvoda u velike gradove kao što je Bogota u Kolumbiji.

Abstract
This paper considers the problem of allocating vehicles to collect and distribute fruit to producer associations in Colombia. In particular, the problem seeks to determine the optimal allocation of vehicles for fruit collection minimising both total transportation costs and CO2 emissions. This problem has multiple objectives, and the well-known e-constraint method has been used as solution technique for the proposed mathematical models. The efficiency of the former methodology has been tested by using a case study involving the distribution of blackberry (Rubus glaucus) by an association of producers in Cundinamarca Department, Colombia. In particular, we considered 12 different scenarios related to supply levels, route outsourcing, and collection frequency. The results show the efficiency of the proposed methodology in solving vehicle allocation problems related to collection and distribution. The case study reveals that, in general, collecting fruit three days/week yields lower costs and fewer emissions than performing collections four days/week. Furthermore, increased supply leads to greater differences between costs and emissions.

Abstract
The irregular strip packing problem consists of cutting a set of convex and non-convex two-dimensional polygonal pieces from a board with a fixed height and infinite length. Owing to the importance of this problem, a large number of mathematical models and solution methods have been proposed. However, only few papers consider that the pieces can be rotated at any angle in order to reduce the board length used. Furthermore, the solution methods proposed in the literature are mostly heuristic. This paper proposes a novel mixed integer quadratically-constrained programming model for the irregular strip packing problem considering continuous rotations for the pieces. In the model, the pieces are allocated on the board using a reference point and its allocation is given by the translation and rotation of the pieces. To reduce the number of symmetric solutions for the model, sets of symmetry-breaking constraints are proposed. Computational experiments were performed on the model with and without symmetry-breaking constraints, showing that symmetry elimination improves the quality of solutions found by the solution methods. Tests were performed with instances from the literature. For two instances, it was possible to compare the solutions with a previous model from the literature and show that the proposed model is able to obtain numerically accurate solutions in competitive computational times.

Abstract
The container loading problem (CLP) is a real-world driven, combinatorial optimisation problem that addresses the maximisation of space usage in cargo transport units. The research conducted on this problem failed to fulfill the real needs of the transportation industry, owing to the inadequate representation of practical-relevant constraints. The dynamic stability of cargo is one of the most important practical constraints. It has been addressed in the literature in an over-simplified way which does not translate to real-world stability. This paper proposes a physics simulation tool based on a physics engine, which can be used to translate real-world stability into the CLP. To validate the tool, a set of benchmark tests is proposed and the results obtained with the physics simulation tool are compared to the state-of-the-art simulation engineering software Abaqus Unified FEA. Analytical calculations have been also conducted, and it was also possible to conclude that the tool proposed is a valid alternative. Copyright © 2017 Inderscience Enterprises Ltd.

Abstract
This paper aims to present, define and structure the car rental fleet management problem, which includes operational fleet management issues and problems traditionally studied under the revenue management framework. The car rental business has challenging and distinctive characteristics, which are mainly related with fleet and decision-making flexibility, and that render this problem relevant for academic research and practical applications. Three main contributions are presented: an in-depth literature review and discussion on car rental fleet and revenue management issues, a novel integrating conceptual framework for this problem, and the identification of research directions for the future development of the field.

Abstract
The European Journal of Operational Research (EJOR) published its first issue in 1977. This paper presents a general overview of the journal over its lifetime by using bibliometric indicators. We discuss its performance compared to other journals in the field and identify key contributing countries/institutions/authors as well as trends in research topics based on the Web of Science Core Collection database. The results indicate that EJOR is one of the leading journals in the area of operational research (OR) and management science (MS), with a wide range of authors from institutions and countries from all over the world publishing in it. Graphical visualization of similarities (VOS) provides further insights into how EJOR links to other journals and how it links researchers across the globe.