bilevel linear programming  is a decision making problem with a two-level decentralized organization. the textquotedblleft leadertextquotedblright~ is in the upper level and the textquotedblleft followertextquotedblright, in the lower. making a decision at one level affects that at the other one. in this paper, bilevel linear programming  with inexact parameters has been studied and a method is...

Optimization in layouts and robot motions is an essential yet challenging task for robotic cell systems crowded spaces. In the conventional research, since posture not explicitly considered, there may be no solution or operation time long if motion optimized layout obtained by arrangement optimization. this work, focusing on importance of posture, we propose a hierarchical optimization framewor...

Optimization is the operation of finding most appropriate solution for a particular problem or set problems. In literature, there are many population-based optimization algorithms solving Each these has different characteristics. Although give optimum results on some problems, they become insufficient to as gets harder and more complex. Many studies have been carried out improve overcome diffic...

1. Abstract In order to make most effective use of an optimization problem formulation within actual design scenarios, the following three goals should be met: (1) acquisition of optimum solutions from wider viewpoints, (2) deepest possible understanding of the achieved optimum design solutions, and (3) breakthrough of the optimum design solutions. This study presents a product design optimizat...

Clustering is often used for discovering structure in data. Clustering systems diier in the objective function used to evaluate clustering quality and the control strategy used to search the space of clusterings. Ideally, the search strategy should consistently construct clusterings of high quality, but be computationally inexpensive as well. In general, we cannot have it both ways, but we can ...

In this paper, we propose a new optimization technique, the hierarchical multi-space competitive distributed genetic algorithm (HmcDGA), which is effective for the hierarchical optimization problem. It is an extension of the multi-space competitive distributed genetic algorithm (mcDGA), which was proposed by the authors. The mcDGA efficiently finds an optimal solution with a low computational c...

In system design, allocation of circuit resources like power and noise budget is a difficult problem. It is difficult to know the optimal distribution of resources because the performance space of each component is not fully characterized. This uncertainty results in an iterative approach with frequent re-design of circuit blocks for different distribution schemes. Equation-based optimization h...