5 resultados para Multi-objective optimization techniques
em Digital Peer Publishing
Resumo:
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.
Resumo:
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.
Resumo:
Die Grundidee hinter dem neuen Regalbediengerät ist die Minimierung der zu bewegenden Last durch die Verwendung einer seilbasierten Stewart-Gough-Plattform (SGP). Das klassische Regalbediengerät (RBG) wird dabei durch eine Plattform ersetzt, die an bis zu acht vorgespannten Seilen befestigt ist. Unterstützt wird diese Bauform durch eine abgestimmte Steuerungssoftware, die es ermöglicht die Vorteile des RBG optimal zu nutzen. Das hier mit Software vorgestellte Konzept regelt die Vorgehensweise zur Optimierung von Ein- und Auslagerungsaufträgen in einem Lagerregal, sowie die Optimierung der Fachbelegung in Zeiten ohne direkten Auftrag. Es beinhaltet dabei Mechanismen, die bestimmen wann Aufträge abgearbeitet werden, in welcher Reihenfolge und in welchen Kombinationen. Ziel ist es Ein- und Auslagerungsaufträge so zu kombinieren, dass möglichst effizient und schnell gearbeitet wird.
Resumo:
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.
Resumo:
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.