Abstract
Several production environments require simultaneous planing of sizing and scheduling of sequences of production lots. Integration of sequencing decisions in lotsizing and scheduling problems has received an increased attention from the research community due to its inherent applicability to real world problems. A two-dimensional classification framework is proposed to survey and classify the main modeling approaches to integrate sequencing decisions in discrete time lotsizing and scheduling models. The Asymmetric Traveling Salesman Problem can be an important source of ideas to develop more efficient models and methods to this problem. Following this research line, we also present a new formulation for the problem using commodity flow based subtour elimination constraints. Computational experiments are conducted to assess the performance of the various models, in terms of running times and upper bounds, when solving real-word size instances.

Abstract
The kidney exchange problem (KEP) is an optimization problem arising in the framework of transplant programs that allow exchange of kidneys between two or more incompatible patient-donor pairs. In this paper an approach based on a new decomposition model and branch-and-price is proposed to solve large KEP instances. The optimization problem considers, hierarchically, the maximization of the number of transplants and the minimization of the size of exchange cycles. Computational comparison of different variants of branch-and-price for the standard and the proposed objective functions are presented. The results show the efficiency of the proposed approach for solving large instances.

Abstract
Logistics network design is a major strategic issue due to its impact on the efficiency and responsiveness of the supply chain. This paper focuses on strategic and tactical design of steel supply chain (SSC) networks. Ever-increasing demand for steel products enforces the steel producers to expand their production and storage capacities. The main purpose of the paper includes preparing a countrywide production, inventory, distribution, and capacity expansion plan to design an SSC network. The SSC networks consist of iron ore mines as suppliers, raw steel producer companies as producers, and downstream steel companies as customers. Demand is assumed stochastic with normal distribution and known at the beginning of planning horizon. To achieve the service level of interest, a potential production capacity along with two kinds of safety stocks including emergency and shared safety stocks are suggested by the authors. A mixed integer nonlinear programming (MINLP) model and a mixed integer linear programming (MILP) model are presented to design dynamic multi-commodity SSC networks. To evaluate the performance of the MILP model, a real case of SSC network design is solved. Furthermore, solving two proposed models by using a commercial solver for a set of numerical test cases shows that the MILP model outperforms MINLP in medium- and large-scale problems in terms of computational time. Finally, the complexity of the linear model is investigated by relaxing some major assumptions.

Abstract
In this paper a constructive heuristic for solving the staff scheduling problem of a glass manufacture unit is proposed. Based on simple calculations and algorithms, the developed procedure assigns working shifts and days-off to teams of employees, ensuring the satisfaction of a mandatory sequence of working shifts and the balance of the workload between employees. The computational times for the experiments with the case study company, with three eight-hour working shifts and five teams of employees, fell consistently below 5 seconds for a set of different planning periods. Results are compared with the ones achieved with an optimization model (MIP), demonstrating the good performance of the heuristic, also in terms of the quality of the achieved solutions. The heuristic rarely fails to produce a feasible solution and whenever the solution is feasible then it is also optimal. When tackling problems with a large number of teams, the heuristic maintains the good performance while the MIP model is not able to find any solution within 16 hours of running time. Although it was designed for a particular problem of the glass industry, tests show that the heuristic is flexible enough to be applied to problems with different features, from other activity sectors, encouraging further extensions of this work.

Abstract
This paper addresses the impact of consumer purchasing behaviour on the production planning of perishable food products for companies operating in the fast moving consumer goods using direct store delivery. The research presented here builds on previous marketing studies related to the effects of expiry dates in order to derive mathematical formulae, which express the age dependent demand for different categories of perishable products. These demand expressions take into account both customer willingness to pay and product quality risk. The paper presents deterministic and stochastic production planning models, which incorporate the customer's eagerness to pick up the fresher products available. Results indicate that model approximations neglecting the fact that customers pick up the fresher products or considering that all products have the same product quality risk have a reduced impact on profit losses. On the other hand, not considering the decreasing customer willingness to pay has an important impact both on the profit losses and on the amount of spoiled products.

Abstract
This paper presents a successful application of operations research techniques in guiding the decision making process to achieve a superior operational efficiency in core activities. We focus on a rich vehicle routing problem faced by a Portuguese food distribution company on a daily basis. This problem can be described as a heterogeneous fleet site dependent vehicle routing problem with multiple time windows. We use the adaptative large neighbourhood search framework, which has proven to be effective to solve a variety of different vehicle routing problems. Our plans are compared against those of the company and the impact that the proposed decision support tool may have in terms of cost savings is shown. The algorithm converges quickly giving the planner considerably more time to focus on value-added tasks, rather than manually correct the routing schedule. Moreover, contrarily to the necessary adaptation time of the planner, the tool is quite flexible in following market changes, such as the introduction of new customers or new products.