The VLSI layout problem in various embedding models

The problem of Unequal Area Facility Layout Planning (UA-FLP) has been addressed by a large number of approaches considering a set of quantitative criteria. Moreover, more recently, the personal qualitative preferences of an expert designer or decision-maker (DM) have been taken into account too. This article deals with capturing more than a single DM’s personal preferences to obtain a common and collaborative design including the whole set of preferences from all the DMs to obtain more complex, complete, and realistic solutions. To the best of our knowledge, this is the first time that the preferences of more than one expert designer have been considered in the UA-FLP. The new strategy has been implemented on a Coral Reef Optimization (CRO) algorithm using two techniques to acquire the DMs’ evaluations. The first one demands the simultaneous presence of all the DMs, while the second one does not. Both techniques have been tested over three well-known problem instances taken from the literature and the results show that it is possible to obtain sufficient designs capturing all the DMs’ personal preferences and maintaining low values of the quantitative fitness function.

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An Optimum Channel Routing Algorithm in the Knock-knee Diagonal Model

VLSI Design ◽

10.1155/1994/19638 ◽

1994 ◽

Vol 1 (3) ◽

pp. 233-242 ◽

Cited By ~ 1

Author(s):

Xiaoyu Song

Keyword(s):

Routing Algorithm ◽

Difficult Problem ◽

Layout Design ◽

Channel Routing ◽

Routing Problem ◽

Vlsi Layout ◽

Channel Density ◽

Optimum Algorithm ◽

Important Time ◽

Optimum Channel

Channel routing problem is an important, time consuming and difficult problem in VLSI layout design. In this paper, we consider the two-terminal channel routing problem in a new routing model, called knock-knee diagonal model, where the grid consists of right and left tracks displayed at +45° and –45°. An optimum algorithm is presented, which obtains d + 1 as an upper bound to the channel width, where d is the channel density.

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Applications of Multiple Objective Genetic Algorithms in the Optimization Design of Tracked Self-Moving Power’s Layout

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.307.161 ◽

2013 ◽

Vol 307 ◽

pp. 161-165

Author(s):

Hai Jin ◽

Jin Fa Xie

Keyword(s):

Optimization Design ◽

Pareto Front ◽

Layout Optimization ◽

Multiple Objective ◽

Multi Objective Optimization ◽

Layout Problem ◽

Basic Principles ◽

Multi Objective ◽

Multi Objective Genetic Algorithm ◽

Set Up

A multi-objective genetic algorithm is applied into the layout optimization of tracked self-moving power. The layout optimization mathematical model was set up. Then introduced the basic principles of NSGA-Ⅱ, which is a Pareto multi-objective optimization algorithm. Finally, NSGA-Ⅱwas presented to solve the layout problem. The algorithm was proved to be effective by some practical examples. The results showed that the algorithm can spread toward the whole Pareto front, and provide many reasonable solutions once for all.

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