[PDF] Top 20 Convalesce Optimization for Input Allocation Problem Using Hybrid Genetic Algorithm
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Convalesce Optimization for Input Allocation Problem Using Hybrid Genetic Algorithm
... search algorithm with some of the innovative flair of human ...solutions. Genetic algorithms were initially developed by John ...development, Genetic Algorithms have been used as optimization ... See full document
4
Hybrid Genetic Algorithms: A Review
... a hybrid genetic algorithm has a great impact on its ...of hybrid genetic algorithms by comparing them with pure genetic ...pure genetic algorithms in evolving the ... See full document
14
Optimization of Turning Operations by Using a Hybrid Genetic Algorithm with Sequential Quadratic Programming
... the optimization problem is to find the solutions of m subproblems, the minimum of these results will be the solution of the global optimization ...3. Genetic algorithm (GA) and ... See full document
7
JISTEM J.Inf.Syst. Technol. Manag. vol.12 número3
... scheduling problem has received considerable attention from both practitioners and ...by using novel heuristic optimization approaches in the multi-objective passenger railway scheduling ... See full document
20
Optimization of transportation channels in supply chain design Using Genetic Algorithm
... a hybrid of NSGA-II and an assignment ...bi-objective optimization model for the design of supply chains considering economic and environmental ...multiobjective optimization techniques as decision ... See full document
9
A hybrid heuristic algorithm for the open-pit-mining operational planning problem
... an optimization system and simulation for analyzing the production scenario in open-pit ...as input for the simulation. The optimization module was developed with the aim of optimizing the process of ... See full document
11
A HYBRID OPTIMIZATION ALGORITHM BASED ON GENETIC ALGORITHM AND ANT COLONY OPTIMIZATION
... Genetic Algorithm (GA) is one of the powerful optimization methods based on the process of natural ...performance problem in GA during the searching, several works have been done aiming at it ... See full document
13
A Bias Random Key Genetic Algorithm for a AGV Scheduling Problem
... existing hybrid system of Volkswagen ...factory using different types of AGVs, with different hardware and software, making the com- munication between AGVs more difficult and, in case of malfunction, the ... See full document
48
HYBRID INVERSION OF INTERVAL VELOCITIES IN MULTISCALE APPROACH
... global optimization algorithms are used commonly in geophysical data ...of algorithm has unique advantages and ...that hybrid algorithms are computationally more efficient than conventional global ... See full document
9
Hybrid Architecture of Genetic Algorithm and Simulated Annealing
... Genetic Algorithm (GA)[1] was proposed by Holland as an algorithm for probabilistic search, learning, and optimization, and is based in part on the mechanism of biological evolution and ... See full document
7
A Genetic Algorithm Approach for Solving a Flexible Job ShopScheduling Problem
... sequencing problem with no machine substitute for each operation while in FJSSP, alternative machines are considered for each ...a genetic algorithm (GA) for solving FJSSP and proved that GA can ... See full document
6
MATERIALS AND METHODS Protocol
... the problem of finding the best approximation to characterize the feet temperature ...nonlinear optimization, specifically the pattern search method for local optimization and the genetic ... See full document
5
Pesqui. Oper. vol.33 número3
... Initially, a set of P chromosomes (individuals) is randomly (uniformly distributed) defined, where each chromosome, x consists of a vector of variables to be optimized, which, in this case, is formed by FCM weights, ... See full document
23
Photoacoustic-based thermal image formation and optimization using an evolutionary genetic algorithm
... GA consisted in generating a population of 100 candidate solutions composted of window length, threshold value, size of moving average mask (width and height) and window overlap. The quality criterion, also known as ... See full document
10
Strength Pareto Evolutionary Algorithm based Multi-Objective Optimization for Shortest Path Routing Problem in Computer Networks
... approximation algorithm (Lawler, ...path problem relying on their parallel architecture to provide a fast solution (Araujo et ...as Genetic Algorithm (GA) (Ahn and Ramakrishna, 2002) and ... See full document
10
J. Aerosp. Technol. Manag. vol.5 número1
... as optimization, reduced costs, sustainability, environment, weight, and ...a problem of combinatorial optimization. As this problem is hard to be solved, several techniques have been ... See full document
8
A genetic algorithm to solve a multi-product distribution problem
... The problem instance used in these experiments was provided by a specific company. Decisions have to be made regarding the quantities to send from a single warehouse to 108 stores. There are eight products to be ... See full document
82
Flow shop scheduling using genetic algorithm
... ,QWKHSUHVHQWVWXG\*$LVDSSOLHGWRVROYHWKHIORZVKRSVFKHGXOLQJSUREOHP'LIIHUHQWVL]HVRISUREOHPV DUHFRQVLGHUHGIRUDQDO\VLV,QLPSOHPHQWLQJ*$VLQJOHSRLQWFURVVRYHUWZRSRLQWFURVVRYHUVKLIWPXWDWLRQDQG UDQG[r] ... See full document
9
Reoptimization of Motif Finding Problem
... discrete optimization problems are NP-Hard, that is we cannot find a polynomial- time algorithm which solves the problem on a Turing Ma- ...measured using an approximation ... See full document
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