this paper considers the job scheduling problem in virtual manufacturing cells (vmcs) with the goal of minimizing two objectives namely, makespan and total travelling distance. to solve this problem two algorithms are proposed: traditional non-dominated sorting genetic algorithm (nsga-ii) and knowledge-based non-dominated sorting genetic algorithm (kbnsga-ii). the difference between these algor...

Studies have shown that multi-objective optimization problems are hard problems. Such problems either require longer time to converge to an optimum solution, or may not converge at all. Recently some researchers have claimed that real culprit for increasing the hardness of multi-objective problems are not the number of objectives themselves rather it is the increased size of solution set, incom...

Target-like echoes from the use of active sonar, known as 'clutter', pose a problem to separate real from false contacts. A method for reducing the amount of clutter in tracking underwater targets is accomplished by using an iterative Multi-Objective Genetic Algorithm (MOGA). The optimization minimizes the position of the genetic population with the last given contact positions, as one objectiv...

The increasing demand for low-cost space-borne Earth observation missions has led to small satellite constellation systems development. CubeSat platforms can provide a cost-effective multiple-mission space system using state-of-the-art technology. This paper presents new approach design multiple multi-objective genetic algorithm (MOGA). is proposed perform multi-missions that should satisfy glo...

This paper presents a novel method of multi-drug scheduling using multi-objective genetic algorithm (MOGA) that can find suitable/optimum dosages by trading-off between cell killing and toxic side-effects of chemotherapy treatment. A close-loop control method, namely Integral-Proportional-Derivative (I-PD) is designed to control dosages of drugs to be infused to the patient’s body and MOGA is u...

This paper studies the problem of routing and wavelength assignment (RWA) in the wavelength division multiplexing (WDM) all-optical networks without wavelength conversion. A new multi-objective integer linear program (MOILP) is proposed for the RWA which seeks to maximize the carried tra±c, minimize the cost, and minimize the required number of wavelengths. The MOILP is solved by a multi-object...

This paper presents the integration between a co-operative co-evolutionary genetic algorithm (CCGA) and four evolutionary multiobjective optimisation algorithms (EMOAs): a multi-objective genetic algorithm (MOGA), a niched Pareto genetic algorithm (NPGA), a nondominated sorting genetic algorithm (NSGA) and a controlled elitist nondominated sorting genetic algorithm (CNSGA). The resulting algori...

Recognising the multiobjective nature of the decision process for rehabilitation of water supply distribution systems, this paper presents a comparative study of two multiobjective evolutionary methods, namely, multiobjective genetic algorithm (MOGA) and strength Pareto evolutionary algorithm (SPEA). The analyses were conducted on a simple hypothetical network for cost minimisation and minimum ...

In this paper, a new approach using a Multi Objective Genetic Algorithm (MOGA) is proposed to determine the optimal state assignment with less area and power dissipations for completely and incompletely specified sequential circuits. The goal is to find the best assignments which reduce the component count and switching activity. The MOGA employs a Pareto ranking scheme and produces a set of st...

delivering perishable products to customers as soon as possible and with the minimum cost has been always a challenge for producers and has been emphasized over recent years due to the global market becoming more competitive. in this paper a multi-objective mix integer non-linear programming model is proposed to maximize both profits of a distributer and the total freshness of the several produ...