Recently, a hybrid methodology for combining genetic algorithms and local search algorithms has received considerable attention. This paper proposes an extended hybrid genetic algorithm to further improve the performance of finding the optimal solution in a large search space. Three key ideas, i.e. the elitism, nonredundant search, and steepest-ascent hill climbing, are introduced into a standa...

In this paper, we present a genetic algorithm with a very small population and a reinitialization process (a micro genetic algorithm) for solving multiobjective optimization problems. Our approach uses three forms of elitism, including an external memory (or secondary population) to keep the nondominated solutions found along the evolutionary process. We validate our proposal using several engi...

The rationale for the thought of an appropriate strategy for social health, issues from the failiure to provide health with social Justice. Too much has been said and done along a devious path by the dominant class, that, increasing marginal rate of disutility threatens the very existence of man. A modest attempt has been made here to expose the corrosion in values and priorities and as to what...

Multi objective optimization is a promising field which is increasingly being encountered in many areas worldwide. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used to solve Multi objective problems. Various multiobjective evolutionary algorithms have been devel...

In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in converging to the Pareto-optimal front (e.g., multimodality and deception). By investigating these diff...

This paper presents ParadisEO-MOEO, a white-box objectoriented generic framework dedicated to the flexible design of evolutionary multi-objective algorithms. This paradigm-free software embeds some features and techniques for Pareto-based resolution and aims to provide a set of classes allowing to ease and speed up the development of computationally efficient programs. It is based on a clear co...

The capacitated multipoint network design problem (CMNDP) is NP-complete. In this paper, a hybrid genetic algorithm for CMNDP is proposed. The multiobjective hybrid genetic algorithm (MOHGA) differs from other genetic algorithms (GAs) mainly in its selection procedure. The concept of subpopulation is used in MOHGA. Four subpopulations are generated according to the elitism reservation strategy,...

This paper presents the simulation of auto-thermal ammonia synthesis reactor. Our target here is to estimate the optimal reactor length which will give the maximum profit from the ammonia reactor. There are many literatures which are interested in ammonia simulation in the past but all need some corrections due to either uncorrected model used or uncorrected algorithm. We used here the ODE45 so...

This paper examines the road train concept as a new alternative in long-distance freight traffic. The design of such a system is a difficult task since many different and conflicting criteria arise depending on the application spectrum, the legal conditions and the preferences of the carrier. Furthermore the evaluation of each decision alternative relies on a time consuming and sophisticated si...

Archives are used in Multi-Objective Evolutionary Algorithms to establish elitism. Depending on the optimization problem, an unconstrained archive may grow to an immense size. With the growing number of nondominated solutions in the archive, testing a new solution for nondominance against this archive becomes the main bottleneck during optimization. As a remedy to this problem, we will propose ...