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نتایج جستجو برای Pareto front

تعداد نتایج: 50243  
Journal: :CoRR 2015
Rüdiger Ehlers,

We give an efficient algorithm to enumerate all elements of a Pareto front in a multi-objective optimization problem in which the space of values is finite for all objectives. Our algorithm uses a feasibility check for a search space element as an oracle and minimizes the number of oracle calls that are necessary to identify the Pareto front of the problem. Given a k-dimensional search space in...

2016
Peter Auer, Chao-Kai Chiang, Ronald Ortner, Madalina M. Drugan,

We consider the problem of identifying the Pareto front for multiple objectives from a finite set of operating points. Sampling an operating point gives a random vector where each coordinate corresponds to the value of one of the objectives. The Pareto front is the set of operating points that are not dominated by any other operating point in respect to all objectives (considering the mean of t...

Journal: :CoRR 2014
Alexander Lavin,

Path planning is one of the most vital elements of mobile robotics. With a priori knowledge of the environment, global path planning provides a collision-free route through the workspace. The global path plan can be calculated with a variety of informed search algorithms, most notably the A* search method, guaranteed to deliver a complete and optimal solution that minimizes the path cost. Path ...

2006
M. Holzer, B. Knerr,

Different implementation possibilities of an algorithm into hardware offer a variety of design solutions. Only best solutions so called pareto optimal solutions are for design decision of interest. Heuristic methods are preferred for the generation of these pareto optimal solutions, because exhaustive search methods cannot efficiently cope with this problem. This paper describes the mapping of ...

2002
Mark Everingham, Henk L. Muller, Barry T. Thomas,

Image segmentation is the first stage of processing in many practical computer vision systems. While development of particular segmentation algorithms has attracted considerable research interest, relatively little work has been published on the subject of their evaluation. In this paper we propose the use of the Pareto front to allow evaluation and comparison of image segmentation algorithms i...

Journal: :Int. J. Computational Intelligence Systems 2012
Chun-Hao Chen, Tzung-Pei Hong, Vincent S. Tseng,

Transactions with quantitative values are commonly seen in real-world applications. Fuzzy mining algorithms have thus been developed recently to induce linguistic knowledge from quantitative databases. In fuzzy data mining, the membership functions have a critical influence on the final mining results. How to effectively decide the membership functions in fuzzy data mining thus becomes very imp...

2013
Hila Sheftel, Oren Shoval, Avi Mayo, Uri Alon,

When organisms perform a single task, selection leads to phenotypes that maximize performance at that task. When organisms need to perform multiple tasks, a trade-off arises because no phenotype can optimize all tasks. Recent work addressed this question, and assumed that the performance at each task decays with distance in trait space from the best phenotype at that task. Under this assumption...

1998
David A. Van Veldhuizen, Gary B. Lamont,

Research into solving multiobjective optimization problems (MOP) has as one of its an overall goals that of developing and defining foundations of an Evolutionary Computation (EC)-based MOP theory. In this paper, we introduce relevant MOP concepts, and the notion of Pareto optimality, in particular. Specific notation is defined and theorems are presented ensuring Paretobased Evolutionary Algori...

Journal: :JORS 2011
Haluk Yapicioglu, H. Liu, Alice E. Smith, Gerry V. Dozier,

Heuristic search can be an effective multi-objective optimization tool; however, the required frequent function evaluations can exhaust computational sources. This paper explores using a hybrid approach with statistical interpolation methods to expand optimal solutions obtained by multiple criteria heuristic search. The goal is to significantly increase the number of Pareto optimal solutions wh...

Journal: :Computers & Industrial Engineering 2014
Jessica L. Chapman, Lu Lu, Christine M. Anderson-Cook,

Pareto front optimization has been commonly used for balancing trade-offs between different estimated responses. Using maximum likelihood or least squares point estimates or the worst case confidence bound values of the response surface, it is straightforward to find preferred locations in the input factor space that simultaneously perform well for the various responses. A new approach is propo...