Abstract
The recent past has shown that many companies stressed from the competition, have reduced manufacturing costs as well implemented sustainable practices as much as possible. And yet this effort has proved to be insufficient. This reality is forcing the companies and managers to address the problem of competitiveness and sustainability in a holistic way, by considering the entire supply chain. Due to this pressure from supply chain stakeholders to a comprehensive sustainability assessment of the entire network, extended “performance metrics” are required not only on the economic value of a business, but also in its environmental and social impacts. Increasing numbers of organizations report a massive volume of data, with low consistency and high variability in data quality, and a dispersion of indicators, making it necessary to develop and implement new approaches for Supply Cain Management (SCM) sustainable performance assessment. This paper focuses on this topic, presenting a new approach for performance and risk assessment within dynamic supply chain networks, supported in a new and comprehensive Sustainability Assessment Framework (SAF).

Abstract
In the ambit of Distribute/Agile/Virtual Enterprises, the resources/partners selection process is a critical issue in order to guarantee the success of such enterprises. The selection process is complex in the large sense of the word and for that we advocate the necessity of a broker to perform that task, conveniently assisted by a tool. In order to contribute to its construction, this paper presents the resolution of a resources system selection problem, designated by Dependent or Integral Selection Method without Pre-selection of Transport Resources, with two algorithms, an exact solution algorithm and an approximate one. The results demonstrate that the exact solution algorithm limitations can be covered by the approximate algorithm. With those results, the broker has the knowledge to perform the selection with the most adequate algorithm for each case of the problem (depending of the number of tasks and pre-selected resources) addressed in this paper. This paper brings a contribution to broker performance for the selection process. (C) 2014 The Authors. Published by Elsevier Ltd.

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.

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
In this article, we review published studies that consider the solution of the one-dimensional cutting stock problem (1DCSP) with the possibility of using leftovers to meet future demands, if long enough. The one-dimensional cutting stock problem with usable leftovers (1DCSPUL) is a problem frequently encountered in practical settings but often, it is not dealt with in an explicit manner. For each work reviewed, we present the application, the mathematical model if one is proposed and comments on the computational results obtained. The approaches are organized into three classes: heuristics, item-oriented, or cutting pattern-oriented. © 2014 Elsevier B.V. All rights reserved.

Abstract
In this paper, we present an integer linear programming model for the vehicle routing problem that considers real-world three-dimensional (3D) loading constraints. In this problem, a set of customers make requests of goods that are wrapped up in boxes, and the objective is to find minimum cost delivery routes for a set of identical vehicles that, departing from a depot, visit all customers only once and return to the depot. Apart from the usual 3D container loading constraints that ensure the boxes are packed completely inside the vehicles and the boxes do not overlap each other in each vehicle, the problem also takes into account constraints related to the vertical stability of the cargo, multidrop situations, and load-bearing strength of the boxes (including fragility). Computational tests with the proposed model were performed using an optimization solver embedded into a modeling language. The results validate the model and show that it is only able to handle problems of a moderate size. However, this model will be useful to motivate other researchers to explore approximate solution approaches to solve this problem, such as decomposition methods, relaxation methods, heuristics, among others, as well as to treat other variants of the problem, such as when time windows or a heterogeneous fleet are present, among others.