This paper presents a Genetic Algorithm (GA) approach for solving constrained reliability optimization problem of the five unit bridge network. Considering uncertainty for cost, the reliability optimization problem has been solved by GA technique to maximize system reliability. GA is an efficient method for solving this type of optimization problems. This paper successfully applies the GA techn...

This paper is concerned with the problem of finding a low-rank solution of an arbitrary sparse linear matrix inequality (LMI). To this end, we map the sparsity of the LMI problem into a graph. We develop a theory relating the rank of the minimum-rank solution of the LMI problem to the sparsity of its underlying graph. Furthermore, we propose three graph-theoretic convex programs to obtain a low...

We give an overview of cone optimization software, with special attention to the differences between the existing packages. We assume the reader is familiar with the theory and algorithms of cone optimization, thus technical details are kept at a minimum. We also outline current research trends and area of potential improvement. 1 Problem description Conic optimization solvers target problems o...

We describe a conic interior point decomposition approach for solving a large scale semidefinite program (SDP) whose primal feasible set is bounded. The idea is to solve such an SDP using existing primal-dual interior point methods, in an iterative fashion between amaster problem and a subproblem. In our case, the master problem is a mixed conic problem over linear and smaller sized semidefinit...

This study presents a new approach based on Tanaka's fuzzy linear regression (FLP) algorithm to solve well-known power system economic load dispatch problem (ELD). Tanaka's fuzzy linear regression (FLP) formulation will be employed to compute the optimal solution of optimization problem after linearization. The unknowns are expressed as fuzzy numbers with a triangular membership function that h...

This chapter discusses several issues related to the design of linguistic models with high interpretability using fuzzy genetics-based machine learning (GBML) algorithms. We assume that a set of linguistic terms has been given for each variable. Thus our modelling task is to find a small number of fuzzy rules from possible combinations of the given linguistic terms. First we formulate a threeob...

Despite convex mathematical optimization methods be applied to general linear optimization problems it can also be applied in a special class of nonlinear optimization. As ambiguity and vagueness are natural and ever-present in real-life situations requiring solutions, it makes perfect sense to attempt to address them using fuzzy convex optimization. In this work, two fuzzy convex approaches ba...

This paper proposes a calibration method for catadioptric camera systems consisting of a surface of revolution mirror and a perspective camera, such as HyperOmni Vision. The proposed method is based on conventional camera calibration and mirror posture estimation. Many methods for camera calibration have been proposed. During the last decade, methods for catadioptric camera calibration have als...

Group technology (GT) is a useful way to increase productivity with high quality in cellular manufacturing systems (CMSs), in which cell formation (CF) is a key step in the GT philosophy. When boundaries between groups are fuzzy, fuzzy clustering has been successfully adapted to solve the CF problem; however, it may result uneven distribution of parts/machines where the problem becomes larger. ...