Abstract

Abstract
As in many other combinatorial optimisation problems, research on nesting problems (aka irregular packing problems) has evolved around the dichotomy between continuous (time consuming) and discrete (memory consuming) representations of the solution space. Recent research has been devoting increasing attention to discrete representations for the geometric layer of nesting problems, namely in mathematical programming-based approaches. These approaches employ conventional regular meshes, and an increase in their precision has a high computational cost. In this paper, we propose a data structure to represent non-regular meshes, based on the geometry of each piece. It supports non-regular discrete geometric representations of the shapes, and by means of the proposed data structure, the discretisation can be easily adapted to the instances, thus overcoming the precision loss associated with discrete representations and consequently allowing for a more efficient implementation of search methods for the nesting problem. Experiments are conducted with the dotted-board model - a recently published mesh-based binary programming model for nesting problems. In the light of both the scale of the instances, which are now solvable, and the quality of the solutions obtained, the results are very promising.

Abstract
Cutting and Packing (C & P) problems arise in many industrial and logistics applications, whenever a set of small items, with different shapes, has to be assigned to large objects with specific shapes so as to optimize some objective function. Besides some characteristics common to combinatorial optimization problems, the distinctive feature of this field is the existence of a geometric subproblem, to ensure that the items do not overlap and are completely contained in the large objects. The geometric tools required to deal with this subproblem depend on the shapes (rectangles, circles, irregular) and on the specific conditions of the problem being solved. In this chapter, after an introduction that describes and classifies Cutting and Packing problems, we review the basic strategies that have appeared in the literature for designing constructive algorithms, local search procedures, and metaheuristics for problems with regular and irregular shapes.

Abstract
Solving nesting problems or irregular strip packing problems is to position polygons on a fixed width and unlimited length strip, obeying polygon integrity containment constraints and non-overlapping constraints, in order to minimize the used length of the strip. To ensure non-overlapping, we use separation lines, i.e., straight lines that separate polygons. We present a nonlinear programming model that considers free rotations of the polygons and of the separation lines. This model uses a considerable smaller number of variables than the few other approaches proposed in the literature. We use the nonlinear programming solver IPOPT (an algorithm of interior points type), which is part of COIN-OR. Computational tests were run using established benchmark instances and the results were compared with the ones obtained with other methodologies in the literature that use free rotations. © 2018 Brazilian Operations Research Society.

Abstract
This paper proposes a logistic planner with supplementary 3D spatial representations to enhance and interact with traditional logistic systems on the context of mobile manipulators performing internal logistics operations. By defining a hierarchical structure, the logistic world model, as the central entity synchronized between multiple system components, the reliability and accuracy of the logistic system is strengthened. The proposed approach aims at implementing a robust and intuitive solution for the set-up of mobile manipulator based logistic systems. The logistic planner includes a web based interface for fast setup of the warehouse layout based on robot sensing, as well as the definition of missions for the fleet of robotic systems.

Abstract
Collaborative networks (CNs) of organizations are nowadays complex and intertwined compositions of technological, cognitive and social artifacts. The design of such compositions should be addressed as a socio-technical endeavor as a way to maximize the success probability. In despite of intensive research in this community, much has to be explored to achieve sound contributions to a design theory of CNs. In this paper, we make use of the context intervention -mechanism-outcome logic (CIMO-logic) as a way to improve the design propositions component of a CN design theory. Variations of the concept of "mechanism" are explored with the goal of making clearer the socio-technical perspective in the design propositions. This theoretical exploration is illustrated with a case of transforming an industrial business association (IBA) in a digital collaborative network.