Abstract
Adsorption equilibrium of fructose, glucose and sucrose was evaluated on sulfonated poly(styrene-co-divinylbenzene) cation-exchange resins. Two types of resins were used: potassium (K(+)) gel-type and sodium (Na(+)) macroporous resins. Influence of the cation and effect of the resin structure on adsorption were studied. The adsorption isotherms were determined by the static method in batch mode for mono-component and multi-component sugar mixtures, at 25 and 40 degrees C, in a range of concentrations between 5 and 250gL(-1). All adsorption isotherms were fitted by a linear model in this range of concentrations. Sugars were adsorbed in both resins by the following order: fructose > glucose > sucrose. Sucrose was more adsorbed in the Na(+) macroporous resin, glucose was identically adsorbed, and fructose was more adsorbed in the K(+) gel-type resin. Data obtained from the adsorption of multi-component mixtures as compared to the mono-component ones showed a competitive effect on the adsorption at 25 degrees C, and a synergetic effect at 40 degrees C. The temperature increase conducted to a decrease on the adsorption capacity for mono-component Sugar mixtures, and to an increase for the multi-component mixtures. Based on the selectivity results, K(+) gel-type resin seems to be the best choice for the separation of fructose, glucose and sucrose, at 25 degrees C.

Abstract
This article addresses several variants of the two-dimensional bin packing problem. In the most basic version of the problem it is intended to pack a given number of rectangular items with given sizes in rectangular bins in such a way that the number of bins used is minimized. Different heuristic approaches (greedy, local search, and variable neighbourhood descent) are proposed for solving four guillotine two-dimensional bin packing problems. The heuristics are based on the definition of a packing sequence for items and in a set of criteria for packing one item in a current partial solution. Several extensions are introduced to deal with issues pointed out by two furniture companies. Extensive computational results on instances from the literature and from the two furniture companies are reported and compared with optimal solutions, solutions from other five (meta) heuristics and, for a small set of instances, with the ones used in the companies.

Abstract
In this paper, a greedy randomized adaptive search procedure (GRASP) for the container loading problem is presented. This approach is based on a constructive block heuristic that builds upon the concept of maximal space, a nondisjoint representation of the free space in a container. This new algorithm is extensively tested over the complete set of Bischoff and Ratcliff problems [Bischoff, E. E., M. S. W. Ratcliff. 1995. Issues in the development of approaches to container loading. Omega 23 377-390], ranging from weakly heterogeneous to strongly heterogeneous cargo, and outperforms all the known nonparallel approaches that, partially or completely, have used this set of test problems. When comparing against parallel algorithms, it is better on average but not for every class of problem. In terms of efficiency, this approach runs in much less computing time than that required by parallel methods. Thorough computational experiments concerning the evaluation of the impact of algorithm design choices and internal parameters on the overall efficiency of this new approach are also presented.

Abstract
Gupta and Magnusson [The capacitated lot-sizing and scheduling problem with sequence-dependent setup costs and setup times. Computers and Operations Research 2005;32(4):727-47] develop a model for the single machine capacitated lot-sizing and scheduling problem (CLSP) with sequence dependent setup times and setup costs, incorporating all the usual features of setup carryovers. In this note we show that this model does not avoid disconnected subtours. A new set of constraints is added to the model to provide an exact formulation for this problem.

Abstract
Inspired by a case study, this paper reports a successful application of VNS to the production planning and scheduling problem that arises in the glass container industry. This is a multi-facility production system, where each facility has a set of furnaces where the glass paste is produced in order to meet the demand, being afterwards distributed to a set of parallel molding machines. Since the neighborhoods used are not nested, they are not ordered by increasing sizes, but by means of a new empirical measure to assess the distance between any two solutions. Neighborhood sizes decrease significantly through-out the search thus suggesting the use of a scheme in which efficiency is placed. over effectiveness in a first step, and the opposite in a second step. We test this variant as well as other two with a real-world problem instance from our case study.

Abstract
Cutting and packing problems involving irregular shapes is an important problem variant with a wide variety of industrial applications. Despite its relevance to industry, research publications are relatively low when compared to other cutting and packing problems. One explanation offered is the perceived difficulty and substantial time investment of developing a geometric tool box to assess computer generated solutions. In this paper we set out to provide a tutorial covering the core geometric methodologies currently employed by researchers in cutting and packing of irregular shapes. The paper is not designed to be an exhaustive survey of the literature but instead will draw on the literature to illustrate the theory and implementation of the approaches. We aim to provide a sufficiently instructive description to equip new and current researchers in the area to select the most appropriate methodology for their needs.