Fuzzy Multi-Objective Linear Programming and Simulation Approach to the Development of Valid and Realistic Master Production Schedule

Master production schedule (MPS) plays an important role in an integrated production planning system. It converts the strategic planning defined in a production plan into the tactical operation execution. The MPS is also known as a tool for top management to control over manufacture resources and becomes input of the downstream planning levels such as material requirement planning (MRP) and capacity requirement planning (CRP). Hence, inappropriate decision on the MPS development may lead to infeasible execution, which ultimately causes poor delivery performance. One must ensure that the proposed MPS is valid and realistic for implementation before it is released to real manufacturing system. In practice, where production environment is stochastic in nature, the development of MPS is no longer simple task. The varying processing time, random event such as machine failure is just some of the underlying causes of uncertainty that may be hardly addressed at planning stage so that in the end the valid and realistic MPS is tough to be realized. The MPS creation problem becomes even more sophisticated as decision makers try to consider multi-objectives; minimizing inventory, maximizing customer satisfaction, and maximizing resource utilization. This study attempts to propose a methodology for MPS creation which is able to deal with those obstacles. This approach takes into account uncertainty and makes trade off among conflicting multi-objectives at the same time. It incorporates fuzzy multi-objective linear programming (FMOLP) and discrete event simulation (DES) for MPS development.

Mathematical methods for the configuration of transportation systems with a focus on continuous and modular matrix conveyors

The lack of flexibility in logistic systems currently on the market leads to the development of new innovative transportation systems. In order to find the optimal configuration of such a system depending on the current goal functions, for example minimization of transport times and maximization of the throughput, various mathematical methods of multi-criteria optimization are applicable. In this work, the concept of a complex transportation system is presented. Furthermore, the question of finding the optimal configuration of such a system through mathematical methods of optimization is considered.

GRASP with Hybrid Path Relinking for Bi-Objective Winner Determination in Combinatorial Transportation Auctions

The procurement of transportation services via large-scale combinatorial auctions involves a couple of complex decisions whose outcome highly influences the performance of the tender process. This paper examines the shipper's task of selecting a subset of the submitted bids which efficiently trades off total procurement cost against expected carrier performance. To solve this bi-objective winner determination problem, we propose a Pareto-based greedy randomized adaptive search procedure (GRASP). As a post-optimizer we use a path relinking procedure which is hybridized with branch-and-bound. Several variants of this algorithm are evaluated by means of artificial test instances which comply with important real-world characteristics. The two best variants prove superior to a previously published Pareto-based evolutionary algorithm.

OCTAVIS: Optimization Techniques for Multi-GPU Multi-View Rendering

We present a high performance-yet low cost-system for multi-view rendering in virtual reality (VR) applications. In contrast to complex CAVE installations, which are typically driven by one render client per view, we arrange eight displays in an octagon around the viewer to provide a full 360° projection, and we drive these eight displays by a single PC equipped with multiple graphics units (GPUs). In this paper we describe the hardware and software setup, as well as the necessary low-level and high-level optimizations to optimally exploit the parallelism of this multi-GPU multi-view VR system.

Educational and Anthropological Perspectives: An Italian View on Migration in Multi-cultural Urban Spaces

In contemporary societies there are different ways to perceive the relation between identity and alterity and to describe the difference between “us” and “them”, residents and foreigners. Anthropologist Sandra Wallman sustains that in multi-cultural urban spaces the frontiers of diversity are not only burdensome markers of identity, but rather they could also represent new chances to define “identity” and “alterity”. These frontiers, in fact, can work like interfaces through which to build time after time, in a creative way, a relationship with the other. From this point of view, the concept of boundary can offer many opportunities to creatively define the relation with the other and to sign new options for cognitive and physical movement. On the other side, in many cases we have a plenty of mechanisms of exclusion that transforms a purely empirical distinction between “us” and “them” in an ontological contrast, as in the case when the immigrant undergoes hostilities through discriminatory language. Even though these forms of racism are undoubtedly objectionable from a theoretical point of view, they are anyway socially “real”, in the sense that they are perpetually reaffirmed and strengthened in public opinion. They are in fact implicit “truths”, realities that are considered objective, common opinions that are part of day-to-day existence. That is the reason why an anthropological prospective including the study of “common sense” should be adopted in our present day studies on migration, as pointed out by American anthropologist Michael Herzfeld. My primary goal is to analyze with such a critical approach same pre-conditions of racism and exclusion in contemporary multi-cultural urban spaces. On the other hand, this essay would also investigate positive strategies of comparing, interchanging, and negotiating alterity in social work. I suggest that this approach can offer positive solutions in coping with “diversity” and in working out policies for recognizing a common identity which, at the same time, do not throw away the relevance of political and economic power.

Collision Detection: Broad Phase Adaptation from Multi-Core to Multi-GPU Architecture

We present in this paper several contributions on the collision detection optimization centered on hardware performance. We focus on the broad phase which is the first step of the collision detection process and propose three new ways of parallelization of the well-known Sweep and Prune algorithm. We first developed a multi-core model takes into account the number of available cores. Multi-core architecture enables us to distribute geometric computations with use of multi-threading. Critical writing section and threads idling have been minimized by introducing new data structures for each thread. Programming with directives, like OpenMP, appears to be a good compromise for code portability. We then proposed a new GPU-based algorithm also based on the "Sweep and Prune" that has been adapted to multi-GPU architectures. Our technique is based on a spatial subdivision method used to distribute computations among GPUs. Results show that significant speed-up can be obtained by passing from 1 to 4 GPUs in a large-scale environment.