نتایج جستجو برای: genetic algorithms ga
تعداد نتایج: 935051 فیلتر نتایج به سال:
being one of the major research fields in the robotics discipline, the robot motion planning problem deals with finding an obstacle-free start-to-goal path for a robot navigating among workspace obstacles. such a problem is also encountered in path planning of intelligent vehicles and automatic guided vehicles (agvs). traditional (exact) algorithms have failed to solve the problem effectively s...
in this paper, we consider a flow shop scheduling problem with availability constraints (fsspac) for the objective of minimizing the makespan. in such a problem, machines are not continuously available for processing jobs due to preventive maintenance activities. we proposed a mixed-integer linear programming (milp) model for this problem which can generate non-permutation schedules. furthermor...
kinetic modeling is an important issue, whose objective is the accurate determination of the rates of various reactions taking place in a reacting system. this issue is a pivotal element in the process design and development particularly for novel processes which are based on reactions taking place between various types of species. the fischer tropsch (ft) reactions have been used as the kineti...
The array factor (sidelobe level, SLL) of a linear array is optimized using modified continuous genetic algorithms in this work. The amplitudes and phases of the currents as well as the separation of the antennas are all taken as variables to be controlled. The results of the design using modified GA versions are compared with other methods. Two design problems were studied using several contin...
This study proposes a modified version of cultural algorithms (CAs) which benefits from rule-based system for influence function. This rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. This is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. This rule ...
No unique method has been so far specified for determining the number of neurons in hidden layers of Multi-Layer Perceptron (MLP) neural networks used for prediction. The present research is intended to optimize the number of neurons using two meta-heuristic procedures namely genetic and hill climbing algorithms. The data used in the present research for prediction are consumption data of water...
task in that good explanations of the positive examples is of more importance tions of genetic algorithms to various research questions in human genetics. 2 Genetic Algorithms, Constraints, and the Knapsack Problem. 10 5.2 Inductive Learning From Examples. 6.3 Genetic Algorithms and Concept Learning. In this paper, we explore Genetic Algorithms (GA) as an alternative approach to derive these mo...
this paper presents a new nonlinear mathematical model to solve a cell formation problem which assumes that processing time and inter-arrival time of parts are random variables. in this research, cells are defined as a queue system which will be optimized via queuing theory. in this queue system, each machine is assumed as a server and each part as a customer. the grouping of machines and parts...
In the GA approach the parameters that influence its performance include population size, crossover rate and mutation rate. Genetic algorithms are suitable for traversing large search spaces since they can do this relatively fast and because the mutation operator diverts the method away from local optima, which will tend to become more common as the search space increases in size. GA’s are base...
in this paper, a multi-product single machine scheduling problem with the possibility of producing defected jobs, is considered. we concern rework in the scheduling environment and propose a mixed-integer programming (mip) model for the problem. based on the philosophy of just-in-time production, minimization of the sum of earliness and tardiness costs is taken into account as the objective fu...
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