Abstract
The load balance aspect of the Container Loading Problem (CLP) has been handled in an simplified way in the literature. Either load balance has been treated as a soft constraint or the geometrical centre of the container has been assumed to be the ideal location for the centre of gravity of the cargo, or both, which does not meet regulatory directives and transportation legislation. In this paper, we treat load balance as a 'hard constraint and adopt vehicle specific diagrams that define the feasibility domain for the location of the centre of gravity of the cargo, according to the vehicle specific technical characteristics, thus fulfilling and complying with real-world regulations and legislation. We propose a multi-population biased random-key genetic algorithm (BRKGA), with a new fitness function that takes static stability and load balance into account. Extensive computational experiments were performed with different variants of the proposed approach. Also solutions taken from the literature were evaluated in terms of load balance. The computational results show that it is possible to obtain stable and load balanced solutions without compromising the performance in terms of container volume utilization, and demonstrate also the advantage in incorporating load balance in the packing generation algorithm.

Abstract
This paper addresses the problem of determining the cutting patterns of metal sheets, which arises in a manufacturer of metal cages, in order to minimize the waste, the number of cuts performed, the number of metal sheets used or a weighted combination of the three. A two stage approach, to solve a 2D guillotine cutting stock problem with single and multiple stock sizes, is presented and compared with the company approach and state-of-the-art algorithms. The results show great improvement compared to the company approach and a very good performance compared to state-of-the-art algorithms.

Abstract
More than ever, the economic globalization is creating the need to increase business competitiveness. Lean manufacturing is a management philosophy oriented to the elimination of activities that do not create any type of value and are thus considered a waste. One of the main differences from other management philosophies is the shop-floor focus and the operators' involvement. Therefore, the training of all organization levels is crucial for the success of lean manufacturing. Universities should also participate actively in this process by developing students' lean management skills and promoting a better and faster integration of students into their future organizations. This paper proposes a single realistic manufacturing platform, involving production and assembly operations, to learn by playing many of the lean tools such as VSM, 5S, SMED, poke-yoke, line balance, TPM, Mizusumashi, plant layout, and JIT/kanban. This simulation game was built in tight cooperation with experienced lean companies under the international program "Lean Learning Academy,"1 and its main aim is to make bachelor and master courses in applied sciences more attractive by integrating classic lectures with a simulated production environment that could result in more motivated students and higher study yields. The simulation game results show that our approach is efficient in providing a realistic platform for the effective learning of lean principles, tools, and mindset, which can be easily included in course classes of less than two hours. © 2013 IEEE.

Abstract
The purpose of this paper is to present the current understanding and con-ceptualization of the cargo stability constraint within the context of the Container Loading Problem. This problem is highly relevant in the transportation industry due to the increasing pressure for a more economically, environmentally and socially efficient and sustainable cargo transportation. Stability is one the most important practical relevant constraints in the Container Loading Problem due to its strong influence on the cargo arrangement. Stability is usually divided into stability during loading operations (static) and stability during transportation (dynamic). Two main contributions are made. Firstly, an overview of recent developments in the literature on the two types of stability, static and dynamic, is provided. Secondly, of opportunities for future research are identified.

Abstract
This work addresses a case study in an intercontinental supply chain. The problem emerges in a company in Angola dedicated to the trade of consumable goods for construction building and industrial maintenance. The company in Angola sends the replenishment needs to a Portuguese company, which takes the decision of which products and in which quantities will be sent by shipping container to the company in Angola. The replenishment needs include the list of products that reached the corresponding reorder point. The decision of which products and in which quantity should take into consideration a set of practical constraints: the maximum weight of the cargo, the maximum volume the cargo and financial constraints related with the minimum value that guarantees the profitability of the business and a maximum value associated with shipping insurance. A 2-stage hybrid method is proposed. In the first stage, an integer linear programming model is used to select the products that maximise the sales potential. In the second stage, a Container Loading Algorithm is used to effectively pack the selected products in the shipping container ensuring the geometrical constraints, and safety constraints such as weight limit and stability. A new set of problem instances was generated with the 2DCPackGen problem generator, using as inputs the data collected in the company. Computational results for the algorithm are presented and discussed. Good results were obtained with the solution approach proposed, with an average occupation ratio of 92% of the container and an average gap of 4% for the solution of the integer linear programming model.

Abstract
This paper presents an integer linear programming (ILP) model to minimise the total energy-cost of a flake ice production unit in food retail stores. This work is based on a real problem in a Portuguese food retail company, where flake ice in necessary throughout the day in order to maintain fresh fish on the shelves at ideal temperature conditions and humidity levels. The proposed approach aims to provide an energy-efficient scheduling of the production to periods with a lower energy cost, as well as to reduce water consumption, by producing the exact quantities required at the right time, minimising waste. The model was tested on a set of real-world instances from the retail company, and on a set of randomly generated instances. The procedure used to create these instances is presented in the paper. For the sets of tested instances, the results show that the model is strong when compared to the lower bounds provided by the linear programming relaxation of the model. The results from the set of real instances show that it is possible to achieve an energy-efficient scheduling of the production which translates in an average annual cost savings of 34.3% for the stores.