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MOTIVATION Repetitive DNA sequences, besides having a variety of regulatory functions, are one of the principal causes of genomic instability. Understanding their origin and evolution is of fundamental importance for genome studies. The identification of repeats and their units helps in deducing the intra-genomic dynamics as an important feature of(More)
— Most real-world search and optimization problems involve multiple conflicting objectives and results in a Pareto-optimal set. Various multi-objective optimization algorithms have been proposed for solving such problems with the goals of finding as many trade-off solutions as possible and maintaining diversity among them. Since last decade, Evolutionary(More)
— Despite the existence of a number of procedures for multi-objective optimization using evolutionary algorithms, there is still the need for a systematic and unbiased comparison of different approaches on a carefully chosen set of test problems. In this paper, a hybrid approach using PCX based NSGA-II and Sequential Quadratic Programming (SQP) is applied(More)
— A new bi-objective optimization problem is formulated for generating the diverse topologies of compliant mechanisms tracing a user-defined path. Motivation behind the present study is to generate the compliant mechanisms which perform the same task of tracing a prescribed trajectory near minimum-weight solution. Therefore, the constraint are imposed at(More)
— This paper presents a multi-objective evolutionary algorithm to solve the day-ahead thermal generation scheduling problem. The objective functions considered to model the scheduling problem are: 1) minimizing the system operation cost and 2) minimizing the emission cost. In the proposed algorithm, the chromosome is formulated as a binary unit commitment(More)
While designing the Compliant Mechanisms (CM), an equal attention is required on both the problem formulation and the optimization algorithm used. Authors of this paper have successfully proposed the formulation of CM tracing user-defined paths based on the precision points. In this paper, authors modify the NSGA-II algorithm by incorporating (i) a helper(More)
This paper presents a new solution to thermal unit-commitment (UC) problem based on a modified hybrid particle swarm optimization (MHPSO). Hybrid real and binary PSO is coupled with the proposed heuristic based constraint satisfaction strategy that makes the solutions/particles feasible for PSO. The velocity equation of particle is also modified to prevent(More)
— The short-term unit commitment problem is traditionally solved as a single-objective optimization problem with system operation cost as the only objective. This paper presents multi-objectivization of the short-term unit commitment problem in uncertain environment by considering reliability as an additional objective along with the economic objective. The(More)
In this paper, we propose a new multi-objective optimization algorithm called Archived-based Stochastic Ranking Evolutionary Algorithm (ASREA) that ranks the population by comparing individuals with members of an archive. The stochastic comparison breaks the usual <i>O</i>(<i>mn</i><sup>2</sup>) complexity into <i>O</i>(<i>man</i>) (<i>m</i> being the(More)