Abstract

Abstract
In the Container Loading Problem literature, the cargo dynamic stability constraint has been evaluated by the percentage of boxes with insufficient lateral support. This metric has been used as a proxy for the real-world dynamic stability constraint and has conditioned the algorithms developed for this problem. It has the advantage of not being expensive from a computation perspective. However, guaranteeing that at least three sides of a box are in contact with another box or with the container wall does not necessarily ensure stability during transportation. In this paper we propose a physics simulation tool based on a physics engine that will be used in the evaluation of the dynamic stability constraint. We compare the results of our physics simulation tool with the state-of-the-art simulation engineering software Abaqus Unified FEA, and conclude that our tool is a promising alternative.

Abstract
Operational planning at public transport companies is a complex process that usually comprises several phases. In the planning phase, schedules are constructed considering that buses arrive and depart as scheduled. Obviously, several disruptions frequently occur, but their impact on the operating conditions is not easy to estimate. This difficulty arises mostly due to the impossibility of testing different solutions under the same conditions. Indeed, typically, the available data are a result of the current plan, while new proposed solutions have not produced real data yet. Along this chapter we discuss the assessment of the impact of changes in the operational planning on the real operating conditions, before their occurrence. We present a framework for such assessment, which includes two components: the impact on costs, and the impact on revenues. We believe that this framework will be useful in future works on operational planning of public transport companies. © Springer International Publishing Switzerland 2014.

Abstract
In this paper, we investigate a two-stage lot-sizing and scheduling problem in a spinning industry. A new hybrid method called HOPS (Hamming-Oriented Partition Search), which is a branch-and-bound based procedure that incorporates a fix-and-optimize improvement method is proposed to solve the problem. An innovative partition choice for the fix-and-optimize is developed. The computational tests with generated instances based on real data show that HOPS is a good alternative for solving mixed integer problems with recognized partitions such as the lot-sizing and scheduling problem.

Abstract
Bonding is an important process used in all fields of industry, where the tight joining of two materials is required. It includes a wide variety of processing technologies that can be placed in a framework of chemistry, physics, and materials science. Although most of these bonding processes have only recently appeared in textbooks, the basic phenomena have been known and used for many centuries. Choosing an appropriate bonding process may result in the improved end-use performance, increased efficiency, and greater design flexibility. Through various bonding techniques, this study aims at investigating the following ones: direct bonding, thermocompression bonding, surface activated bonding, eutectic bonding, adhesive bonding, and glass frit bonding. The characteristic features of these techniques with respect to their many-sided aspects and a review of the current state of the art of each technique are briefly outlined in this chapter.

Abstract
Background: As patient's length of stay in waiting lists increases, governments are looking for strategies to control the problem. Agreements were created with private providers to diminish the workload in the public sector. However, the growth of the private sector is not following the demand for care. Given this context, new management strategies have to be considered in order to minimize patient length of stay in waiting lists while reducing the costs and increasing (or at least maintaining) the quality of care. Method: Appointment scheduling systems are today known to be proficient in the optimization of health care services. Their utilization is focused on increasing the usage of human resources, medical equipment and reducing the patient waiting times. In this paper, a simulation-based optimization approach to the Patient Admission Scheduling Problem is presented. Modeling tools and simulation techniques are used in the optimization of a diagnostic imaging department. Results: The proposed techniques have demonstrated to be effective in the evaluation of diagnostic imaging workflows. A simulated annealing algorithm was used to optimize the patient admission sequence towards minimizing the total completion and total waiting of patients. The obtained results showed average reductions of 5% on the total completion and 38% on the patients' total waiting time.