Evolutionary Multi-Objective Algorithm
Incorporation of decision maker preferences in an interactive evolutionary multi objective algorithm using a multi criteria sorting
... The interactive approach depends on the progressive definition of the DM’s preferences, together with the exploration of the objective space. Articulation of preferences is performed during the optimization ...
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Evolving temporal fuzzy itemsets from quantitative data with a multi objective evolutionary algorithm
... genetic algorithm was used to evolve attribute intervals with each attribute directly represented in the chromosome, which differs from the variable number of attributes used in this ...approach. ...
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A Problem Specific Multi objective Evolutionary Algorithm
... MOEA/D based on decomposition shows efficiency in solving multi-objective problems, but there are some drawbacks: 1 The efficiency of getting new promising solutions is low; 2 Because th[r] ...
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Software Module Clustering using a Fast Multi-objective Hyper-heuristic Evolutionary Algorithm
... The Multi- objective Hyper-heuristic Evolutionary Algorithm (MHypEA) is a fast and effective metaheuristic search technique for suggesting software module clusters while maximizing cohesion ...
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Sequential multi-objective evolutionary algorithm for a real-world water distribution system design
... genetic algorithm technique to optimize the number and location of control valves for pressure control decreasing the leakage amount ...using multi objective algorithm such as genetic ...
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Solving Vehicle Routing Problem with Proposed Non Dominated Sorting Genetic Algorithm and Comparison with Classical Evolutionary Algorithms
... Genetic Algorithm (NSGA) has established itself as a benchmark algorithm for Multi objective ...basic algorithm for big problem gives less efficient results, which renders it less ...
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A Multi-objective Optimization of Sino-Kazakh Container Flow through Dostyk-Alashankou Node of the New Eurasian Land BridgeKsenia K. A. Novikova MEng, Lu Jing, Otieno R. Kennedy MEng
... Various multi-objective evolutionary algorithms have been developed to efficiently solve optimization problems especially in railway networks (Vrugt and Robinson 2007; Chen and Mahfouf 2006; Tan et ...
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Multi indicators Multi objective Evolutionary Algorithm with Q Learning for Real world Network Optimization
... In multi-objective optimizations, a final solution set is usually evaluated according to a variety of ...complex multi-objective optimization ...the algorithm based on a single ...
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A multi-objective Pareto ant colony algorithm for the Multi-Depot Vehicle Routing problem with Backhauls Pages 35-48 Download PDF
... for multi-objective problems were presented in Jozefowiez et ...the multi-objective evolutionary algorithms was proposed by Zhou et ...the multi-objective version of the ...
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A Systematic Literature Review- SLR On Recent Advances And Variants Of Grey Wolf Optimization
... as multi-objective grey wolf optimization to solve the multi- objective optimization issue for the first ...This multi- objective grey wolf optimization result compare with other ...
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A New Multi Objective Genetic Algorithm for Use in Investment Management
... - A posteriori preference articulation: the decision-maker is not capable to specify in advance the relative importance (by setting the weighting factors) of the objective functions. Once the set of non-dominated ...
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Three decades of the Shuffled Complex Evolution (SCE-UA) optimization algorithm: Review and applications
... optimization algorithm, initially developed by Duan et ...optimization algorithm, it has found widespread applications across a diverse range of science and engineering ...SCE-UA algorithm and its ...
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An alternative hybrid evolutionary technique focused on allocating machines and sequencing operations Pages 585-596 Download PDF
... genetic algorithm, yielding good solutions and minimizing the makespan and the workload of the ...the evolutionary algorithm is complemented by learning under schemes and composite dispatch ...
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Learning automata and sigma imperialist competitive algorithm for optimization of single and multi-objective functions
... one objective or numbers of objectives with the same ...is multi objective problems (MOPs) which have at least two conflicting ...new evolutionary based algorithms have been proposed to tackle ...
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Multi-Objective Sentiment Analysis Using Evolutionary Algorithm for Mining Positive & Negative Association Rules
... existing algorithm is used for comparing and analyzing the performance of newly proposed ...existing algorithm MOPNAR, only concentrated on the positive quantitative association rules, but this proposed ...
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Solving Multi-objective Optimal Control Problems of chemical processes using Hybrid Evolutionary Algorithm
... Genetic Algorithm (NSGA) was introduced by Srinivas and Deb [35] ...solve multi- objective optimization problems . This algorithm identifies non-dominated solutions in the population , at each ...
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Evolving temporal fuzzy association rules from quantitative data with a multi objective evolutionary algorithm
... Extracting a set of fuzzy association rules from areas of the dataset where the occurrence is greater is treated as a multi-objective problem. This is the optimisation of two or more functions, whilst ...
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Multi-Objective Optimization to Workflow Grid Scheduling using Reference Point based Evolutionary Algorithm
... The Multi-Objective Evolutionary Algorithms (MOEAs) are the effective way to solve multi-objective optimization problem like scheduling in ...one objective with respect to ...of ...
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Safety Management in NPPs Using Evolutionary Algorithm
... The multi objective optimization at the plant level for the risk vs. cost/hr of maintaining the risk level due to a particular initiating event LOCA and MSLB are given in figure-4&5 respectively. The ...
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Modified NSGA II for a Bi Objective Job Sequencing Problem
... popular Multi-objective Evolutionary Algorithm (MOEA) known as NSGA-II (Non-Dominated Sorting Genetic Algorithm-II) [28] is ...The algorithm for the modified NSGA-II is shown in ...
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