Abstract
In this paper, we present a novel mixed integer linear programming (MIP) model to solve the problem of storage space optimization in a port grain cereal silo. This work is based on a real case study for scheduling storage operations in a port cereal silo, where schedulers are faced daily with the problem of finding the best solution for transfers between storage cells, to maximize the number of empty cells, in order to have greater capacity to receive new lots, subject to storage and transportation lines capacity constraints, and receiving dispatching plans. The problem is formulated by a mixed integer linear programming model and implemented in an Excel/VBA platform. The results show that the model optimizes the number of empty cells, in computational time less than 60 seconds, and thereby constitutes a significant added value to the concerned company. © 2015 Taylor & Francis Group, London.

Abstract
This paper studies a real world dedicated parallel machine scheduling problem with sequence dependent setups, different machine release dates and additional resources (PMSR). To solve this problem, two previously proposed models have been adapted and a novel objective function, the minimisation of the sum of the machine completion times, is proposed to reflect the real conditions of the manufacturing environment that motivates this work. One model follows the strip-packing approach and the other is time-indexed. The solutions obtained show that the new objective function provides a compact production schedule that allows the simultaneous minimisation of machine idle times and setup times. In conclusion, this study provides valuable insights into the effectiveness of different models for solving PMSR problems in real-world contexts and gives directions for future research in this area using complementary approaches such as matheuristics.

Abstract
The problem of routing and scheduling of technicians is a problem that technical assistance and maintenance companies face nowadays, market competitiveness requires quick response, service diversification, and customer satisfaction. The relationship between competitiveness and profitability of companies involves the effective management of their resources. The work developed addresses a real problem of a major Portuguese company providing technical assistance to the home, a varied set of services (need for specific skills and execution times) must be scheduled for a set of technicians with heterogeneous skills and geographical locations (start and end of the route) based on their different places of residence. The results show a considerable increase in the efficiency levels of the solution obtained when compared to the company's current solution and reveals that the lack of homogeneity of skills among technicians and the variation in service flows are factors that should be considered in the operational management of resources and the contracting of work, and that the increase in working hours can also contribute to improving the efficiency of the process.

Abstract
Production scheduling generates a direct impact on several aspects of manufacture, such as the number of delays in delivery to customers, total flow time, as well as the percentage of equipment used. It must, therefore, constitute a priority in production management, which should seek to implement scheduling techniques that will lead to positive results from the perspective of the quality of the solution. However, the methodology cannot overlook the functional aspect of the time which has elapsed until the solution is reached. This study is based on a real and specific module software improvement into a company devoted to the development of ERP software systems (Enterprise Resource Planning). It presents a solution for the production scheduling module focused on flow-shop operations, comprising a total of nine dispatching rules. An additional solution for scheduling is also proposed, which resorts to metaheuristic simulated annealing. Both solutions are compared to each other by using the quality-functionality binomial approach. These two environments are further contrasted with a third, where no effective solution for production scheduling exists. The environment which includes scheduling through dispatching rules was compared to the environment where no production scheduling was implemented. The results obtained from this analysis show an improvement of 13%. The simulated annealing solution presents an improvement of 3,6% when compared to a solution which uses dispatching rules. This improvement implies one extra minute in the calculation of the final solution.

Abstract
The global economic crisis makes it necessary to increase business competitiveness. Lean is a manufacturing philosophy that deserves the attention of employers and their employees, since its objectives are to increase productivity, reduce waste, and optimize available resources. The 5S method is a lean tool that can improve productivity by improving the organization of the workplace. A brief survey of the market showed that there are several organizations dedicated to training and sharing this type of knowledge but only a few of them have digital tools available. Therefore, the use of a digital serious game that helps to understand the 5S method can effectively support an alternative form of learning. This article proposes a serious game that aims to respond to this need. This practical approach encourages the player to learn by trial and error. Information displayed throughout the game enhances learning, without a cognitive overload for the player. The game's evaluation has shown that our approach is efficient and results in the learning of 5S concepts. © 2013 IEEE.

Abstract
In this paper we present a hybrid exact-heuristic method to improve a branch-and-price algorithm to solve the unrelated parallel machines with sequence-dependent setup times scheduling problem. As most of the computational time in the column generation (CG) process is spent in subproblems, two new heuristics to solve the subproblems are embedded in the branch-and-price (BP) framework with the aim to improve the efficiency of the process in obtaining optimal solutions. Computational results show that the proposed method improves a state-of-the-art BP algorithm from the literature, providing optimal solutions for large instances (e. g. 50 machines and 180 jobs) of the parallel machine scheduling problem with sequence dependent setup times, in significantly less time. One of the proposed approaches reduces, in average, to a half the time spent in the root of the branch-and-price tree and to a quarter the time spent in the full branch-and-price algorithm.