This paper studies fitness inheritance as an efficiency enhancement technique for genetic and evolutionary algorithms. Convergence and population sizing models are derived and compared with experimental results. These models are optimized for greatest speed-up and the optimal inheritance proportion to obtain such a speed-up is derived. Results also show that when the inheritance effects are con...

We develop a risk-sensitive strategic facility sizing model that makes use of readily obtainable data and addresses both capacity and responsiveness considerations. The solution is generally robust to demand forecast uncertainty, which is important since capacity planning must be done at a stage when demand forecasts are necessarily poor. The model also leads to managerial insights, including: ...

This paper proposes a stochastic optimization method, based on ant colony optimization, for the optimal choice of transformer sizes to be installed in a distribution network. This method is properly introduced to the solution of the optimal transformer sizing problem, taking into account the constraints imposed by the load the transformer serves throughout its life time and the possible transfo...

Abstrecr-Given a sliceable floorplan and cell sizes, Otten and Stockmeyer [12], [13] presented an algorithm to find an optimal implementation for each cell. We consider a generalized optimal sizing problem on a set of slicing trees related to an adjacency graph. For computation efficiency, we combine the tree enumeration and sizing procedures in a unified algorithm where floorplan trees and siz...

This paper presents a congestion management methodology in deregulated power systems by optimal location and sizing of Unified Power Flow Controller (UPFC) in a transmission network. A multiobjective optimization problem has been developed by considering total congestion cost, power loss and system severity. A Fuzzy based approach has been proposed to identify the optimal location and sizing of...

This paper proposes a general architecture for using evolutionary algorithms to achieve MEMS design synthesis. Functional MEMS devices are designed by combining parameterized basic MEMS building blocks together using Multi-objective Genetic Algorithms (MOGAs) to produce a pareto optimal set of feasible designs. The iterative design synthesis loop is implemented by combining MOGAs with the SUGAR...