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
In production planning in the glass container industry, machine-dependent setup times and costs are incurred for switch overs from one product to another. The resulting multi-item capacitated lot-sizing problem has sequence-dependent setup times and costs. We present two novel linear mixed-integer programming formulations for this problem, incorporating all the necessary features of setup carryovers. The compact formulation has polynomially many constraints, whereas the stronger formulation uses an exponential number of constraints that can be separated in polynomial time. We also present a five-step heuristic that is effective both in finding a feasible solution (even for tightly capacitated instances) and in producing good solutions to these problems. We report computational experiments.

Abstract
The GRMODGRASP, a new algorithm for the container-loading problem (CLP) based on the greedy randomized adaptive search procedure (GRASP) approach, is discussed. Based on a wall-building, constructive heuristic, it can achieve high levels of cargo stability without compromising the container's volume use. The algorithm builds a solution, and then it improves the solution with a local-search algorithm. If it finds a better solution, this new solution replaces the old and a new neighborhood is built around it. The algorithm uses a first better strategy when more than one better solution exists.

Abstract
Cutting and packing problems have been a core area of research for many decades. Irregular shape packing is one of the most recent variants to be widely researched and its history extends over 40 years. The evolution of solution approaches to this problem can be attributed to increased computer power and advances in geometric techniques as well as more sophisticated and insightful algorithm design. In this paper we will focus on the latter. Our aim is not to give a chronological account or an exhaustive review, but to draw on the literature to describe and evaluate the core approaches. Irregular packing is combinatorial and as a result solution methods are heuristic, save a few notable exceptions. We will explore different ways of representing the problem and mechanisms for moving between solutions. We will also propose where we see the future challenges for researchers in this area.

Abstract
The purpose of this paper is to present a methodology that allows higher education institutions (HEIs) to promote, to evaluate and to report on sustainability. The ultimate goal of the afore-mentioned methodology is to help HEIs achieve sustainability. First, a model entitled Sustainability in Higher Education Institutions (SusHEI) that generally describes and characterizes the functioning of an HEI was defined. SusHEI takes into account the core activities of any HEI (education and research), its impacts at economic, environmental and social levels, and the role of its community. SusHEI allowed for the establishment of internal dimensions interrelated to the functioning of an HEI. Then, a matricial representation of the model was developed. The matrix crosses internal dimensions (and eventually sub-dimensions) with sustainability dimensions (and eventually sub-dimensions) and it is quantified through indicators. There is a wide range of possible sustainability indicators that can be chosen, depending on the purpose and the public to whom the indicators/reports are addressed. The methodology is illustrated by a case-study - the Faculty of Engineering of the University of Porto (FEUP). This paper provides a methodology that enables the selection of sustainability indicators for sustainability reporting, assessment or even for benchmarking, and also eliminates some of the main weaknesses found in the models currently available. Higher Education Policy (2011) 24, 459-479. doi:10.1057/hep.2011.18