نتایج جستجو برای: dominated sort genetic algorithm
تعداد نتایج: 1382249 فیلتر نتایج به سال:
The following MOEA algorithms are briefly summarized and compared: • NPGA Niched Pareto Genetic Algorithm (1994) – NPGA II (2001) • NSGA Non-dominated Sorting Genetic Algorithm (1994) – NSGA II (2000) • SPEA Strength Pareto Evolutionary Algorithm (1998) – SPEA2 (2001) – SPEA2+ (2004) – ISPEA Immunity SPEA (2003) • PAES Pareto Archived Evolution Strategy (2000) – M-PAES Mimetic PAES (2000) • PES...
multiple traveling salesman problem (mtsp) is one of the most popular operation research problem and is known as combinatorial optimization problems. mtsp is an extension version of the famous and widely used problem named traveling salesman problem (tsp). because of its benefices in various domains, many researchers have tried to solve that, and many methods have proposed so far. mtsp is a np-...
clustering is the process of dividing a set of input data into a number of subgroups. the members of each subgroup are similar to each other but different from members of other subgroups. the genetic algorithm has enjoyed many applications in clustering data. one of these applications is the clustering of images. the problem with the earlier methods used in clustering images was in selecting in...
the aim of this paper is to present an efficient method for a rail freight car fleet sizing problem. this problem is modeled mathematically as a multi-period, dynamic and multi-objective, in which the rail freight wagons are assumed to be heterogeneous. demands for different wagons and all travel times are assumed deterministic. in order to increase the utilization of the available wagons in th...
a multi-objective optimization procedure has been developed to determine some kinetic parameters of free radical polymerization of vinyl acetate based on genetic algorithm. for this purpose, mathematical modeling of free radical polymerization of vinyl acetate is carried out first and then selected kinetic parameters are optimized by minimizing objective functions defined from comparing experim...
In this paper, one of the evolutionary algorithm based method, Non-Dominated Sorting Genetic Algorithm (NSGA) has been presented for the Volt / Var control in power distribution systems with dispersed generation (DG). The proposed method is better suited for volt/var control problems. Genetic algorithm approach is used due to its broad applicability, ease of use and high accuracy. A multi-objec...
Sorting is a commonly used operation in computer science. In addition to its main job of arranging lists or arrays in sequence, sorting is often also required to facilitate some other operation such as searching, merging and normalization or used as an intermediate operation in other operations. A sorting algorithm consists of comparison, swap, and assignment operations[1-3]. There are several ...
Multi-objective optimization (MO) is a highly demanding research topic because many realworld optimization problems consist of contradictory criteria or objectives. Considering these competing objectives concurrently, a multi-objective optimization problem (MOP) can be formulated as finding the best possible solutions that satisfy these objectives under different tradeoff situations. A family o...
This paper addresses an unrelated multi-machine scheduling problem with sequence-dependent setup time, release date and processing set restriction to minimize the sum of weighted earliness/tardiness penalties and the sum of completion times, which is known to be NP-hard. A Mixed Integer Programming (MIP) model is proposed to formulate the considered multi-criteria problem. Also, to solve the mo...
This paper proposes a Trust-Region Based Augmented Method (TRALM) to solve a combined Environmental and Economic Power Dispatch (EEPD) problem. The EEPD problem is a multi-objective problem with competing and non-commensurable objectives. The TRALM produces a set of non-dominated Pareto optimal solutions for the problem. Fuzzy set theory is employed to extract a compromise non-dominated sol...
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