نتایج جستجو برای: dominance based genetic algorithm
تعداد نتایج: 3828925 فیلتر نتایج به سال:
this paper deals with a multi-period fixed charge production-distribution problem associated with backorder and inventories. the objective is to determine the size of the shipments from each supplier and backorder and inventories at each period, so that the total cost incurred during the entire period towards production, transportation, backorder and inventories is minimised. a 0-1 mixed intege...
For the purpose of graphical analysis and estimation of genetic parameters related to yield and its components, six tobacco genotypes was crossed in half -diallel mating design. In this study, the F2 progenies and their parents were evaluated in a randomized complete block design with three replications. The results of analysis of variance indicated a significant difference between genotypes fo...
Bankruptcy is an event with strong impacts on management, shareholders, employees, creditors, customers and other stakeholders, so as bankruptcy challenges the country both socially and economically. Therefore, correct prediction of bankruptcy is of high importance in the financial world. This research intends to investigate financial crisis prediction power using models based on Neural Network...
Optimisation of stacking sequence for composite plates under slamming impact loads using genetic algorithm method is studied in this paper. For this purpose, slamming load is assumed to have a uniform distribution with a triangular-pulse type of intensity function. In order to perform optimisation based on the genetic algorithm method, a special code is written in MATLAB software environment. T...
In this paper, we propose a constraint-handling approach for genetic algorithms which uses a dominance-based selection scheme. The proposed approach does not require the fine tuning of a penalty function and does not require extra mechanisms to maintain diversity in the population. The algorithm is validated using several test functions taken from the specialized literature on evolutionary opti...
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-...
implicit and unobserved errors and vulnerabilities issues usually arise in cryptographic protocols and especially in authentication protocols. this may enable an attacker to make serious damages to the desired system, such as having the access to or changing secret documents, interfering in bank transactions, having access to users’ accounts, or may be having the control all over the syste...
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...
Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...
bankruptcy is an event with strong impacts on management, shareholders, employees, creditors, customers and other stakeholders, so as bankruptcy challenges the country both socially and economically. therefore, correct prediction of bankruptcy is of high importance in the financial world. this research intends to investigate financial crisis prediction power using models based on neural network...
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