Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In mos...

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...

In many real-world applications, various optimization problems with conflicting objectives are very common. In this paper we employ Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), a newly developed method, beside Tabu Search (TS) accompaniment to achieve a new manner for solving multi-objective optimization problems (MOPs) with two or three conflicting objectives. This i...

Evolutionary Algorithms are recognized to be efficient to deal withMulti-objective Optimization Problems(MOPs) which are difficult to be solved with traditional methods. Here a newMulti-objective Optimization Evolutionary Algorithm named DGPS which is compound with Geometrical Pareto Selection Method (GPS), Weighted SumMethod (WSM) and Dynamical Evolutionary Algorithm (DEA) is proposed. Some fa...

This paper presents a Multi-objective Evolutionary Algorithm (MOEA) to derive a set of optimal operation policies for a multipurpose reservoir system. One of the main goals in multiobjective optimization is to find a set of well distributed optimal solutions along the Pareto front. Classical optimization methods often fail in attaining a good Pareto front. To overcome the drawbacks faced by the...

A Genetic Algorithm (GA) is the process of constructing an optimization problem in which several objectives can be optimized at the same time. In this paper, Strength Pareto Evolutionary Algorithm (SPEA), a GA based multi-objective optimization technique, has been applied to a graph drawing (GD) problem. In this paper a measure (force equalization) which contributes to production of nicely draw...

⎯ The integrated control of voltage and reactive power (volt/var) on radial distribution feeder is formulated as a multiobjective optimization problem to be solved trough the Strength Pareto Evolutionary Algorithm (SPEA2), a relatively recent technique of recognized computational efficiency. Two objectives has been established: voltage level variation and power and energy losses including costs...

In this paper, a multipath routing scheme is proposed for data transmission in a packet-switched network to improve the reliability of data delivery to multicast destinations, and to reduce network congestion. A multi-objective optimization model is presented that utilizes FEC (Forward Error Correction) across multiple multicast trees for transmitting packets toward the destinations. This model...