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...

Recent SVD-free matrix factorization formulations have enabled rank optimization for extremely large-scale systems (millions of rows and columns). In this paper, we consider rank-regularized formulations that only require a target data-fitting error level, and propose an algorithm for the corresponding problem. We illustrate the advantages of the new approach using the Netflix problem, and use ...

As additive manufacturing expands into multi-material, there is a demand for efficient multi-material topology optimization, where one must simultaneously optimize the topology, and the distribution of various materials within the topology. The classic approach to multi-material optimization is to minimize compliance or stress while imposing two sets of constraints: (1) a total volume constrain...

Pareto-optimal Nash equilibrium is a refinement of the Nash equilibrium. An evolutionary method is described in order to detect this equilibrium. Generative relations induces a non-domination concept which is essentially in the detection method. Numerical experiments with games having multiple Nash equilibria are presented. The evolutionary method detects correctly the Pareto-optimal Nash equil...

Leakage power consumption of current CMOS technology is already a great challenge. ITRS projects that leakage power consumption may come to dominate total chip power consumption as the technology feature size shrinks. Leakage is a serious problem particularly for SRAM which occupies large transistor count in most state-of-the-art chip designs. We propose a novel ultralow leakage SRAM design whi...

Evolutionary multiobjective optimization has become a very popular topic in the last few years. Since the 1980s, various evolutionary approaches that are capable of searching for multiple solutions simultaneously in a single run have been developed to solve multiobjective optimization problems (MOPs). However, to find a uniformly distributed, near-complete, and near-optimal Pareto front in a sm...

In this paper, a novel multiobjective evolutionary algorithm for optimal reactive power (VAR) dispatch problem is presented. The optimal VAR dispatch problem is formulated as a nonlinear constrained multiobjective optimization problem where the real power loss and the bus voltage deviations are to be minimized simultaneously. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is...

Owing to the incremental demands for electrical energy, distributed generation (DG) sources are becoming more important in distribution systems. Locations and capacities of DG sources have profoundly impacted on the system losses in a distribution network. In this paper, a novel Strength Pareto Evolutionary Algorithm (SPEA) is represented for optimal location and sizing of DG on distribution sy...