Convergence analyses of evolutionary multiobjective optimization algorithms typically deal with the convergence in limit (stochastic convergence) or the run time. Here, for the first time concrete results for convergence rates of several popular algorithms on certain classes of continuous functions are presented. We consider the algorithms in the version of using a (1+1) selection scheme. Then,...

A new evolutionary multi-objective crowding algorithm (EMOCA) is evaluated using nine benchmark multiobjective optimization problems, and shown to produce non-dominated solutions with significant diversity, outperforming state-of-the-art multi-objective evolutionary algorithms viz., Non-dominated Sorting Genetic Algorithm – II (NSGA-II), Strength Pareto Evolutionary algorithm II (SPEA-II) and P...

Algorithms developed for scheduling applications on heterogeneous multiprocessor system focus on a single objective such as execution time, cost or total data transmission time. However, if more than one objective (e.g. execution cost and time, which may be in conflict) are considered, then the problem becomes more challenging. This project is proposed to develop a multiobjective scheduling alg...

The design of adsorption systems for separation CO2/N2 in carbon capture applications is notoriously challenging because it requires constrained multiobjective optimization to determine appropriate combinations a moderately large number system operating parameters. status quo the literature use nondominated sorting genetic algorithm II (NSGA-II) solve problem. This approach 1000s time-consuming...

Nowadays, manufacturing enterprises face the challenge of just-in-time (JIT) production and energy saving. Therefore, study of JIT production and energy consumption is necessary and important in manufacturing sectors. Moreover, energy saving can be attained by the operational method and turn off/on idle machine method, which also increases the complexity of problem solving. Thus, most researche...

Wireless Mesh Networks are an attractive technology for providing broadband connectivity to mobile clients who are just on the edge of wired networks, and also for building self organized networks in places where wired infrastructures are not available. Routing in Wireless Mesh Networks has multiobjective nonlinear optimization problem with some constraints. This problem has been addressed by c...

<span id="docs-internal-guid-a50ef6a8-7fff-b6d7-8e58-d434be6097d4"><span>This paper proposes a novel approach based on the NSCE (elitist non dominated sorting cross entropy), for optimization of location and size flexible AC transmission system device (FACTS) namely: unified power flow controller (UPFC) to achieve optimal reactive (ORPF). In present work, main objective is minimize ...

Current tools and techniques devoted to examine the content of large databases are often hampered by their inability to support searches based on criteria that are meaningful to their users. These shortcomings are particularly evident in data banks storing representations of structural data such as biological networks. Conceptual clustering techniques have demonstrated to be appropriate for unc...

The nature of optimization for intermittent sugar cane crystallization process is to obtain ideal crystals. One typical difficulty in crystallization optimization refers to the simultaneous effects of both seeding characters and process variables on the final crystal size distribution (CSD) parameters, including mean size (MA) and coefficient of variation (CV). And the application of traditiona...

Epistasis and NK-Landscapes in the context of multiobjective evolutionary algorithms are almost unexplored subjects. Here we present an extension of Kauffman’s NK-Landscapes to multiobjective MNK-Landscapes in order to use them as a benchmark tool and as a mean to understand better the working principles of multiobjective evolutionary algorithms (MOEAs). In this work we present an elitist multi...