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What is Simons decision-making model?

January 14, 2011 4:56PM

Simon's Model is based on premise that decision rash null. Decision making in Simon's Model is characterized by limited information processing and use of rules. Simmons decision-making model there are four phases

1) Intelligence phase

2) Design phase

3) Choice phase

4) Implementation phase

Initially the problem comes and we are in the intelligence phase thinking of the problem as it comes and then we try to find out what the solution to the given problem and then we move to design phase. In the design phase the way and method to solve the problem is thought and we actually try analyze the problem, we try to find the algorithms and the way that can actually solve the problem and hence we use the genetic algorithm to find the solution to the given problem .After finding the method which is to be applied to the given problem we move to choice phase and here the actual work of finding the best algorithm come .Here we try to find the best algorithm from the given set of algorithm we have the option of choosing the algorithms such as "ACO" algorithm which is called the ant colony optimization algorithm or we have the choice of finding the algorithm such as Simulated annealing (SA) is a related global optimization technique that traverses the search space by testing random mutations on an individual solution. A mutation that increases fitness is always accepted. A mutation that lowers fitness is accepted probabilistically based on the difference in fitness and a decreasing temperature parameter. In SA parlance, one speaks of seeking the lowest energy instead of the maximum fitness. SA can also be used within a standard GA algorithm by starting with a relatively high rate of mutation and decreasing it over time along a given schedule. After deciding that genetic algorithm is the most suitable algorithm for the programming we move to the next step which is the implemetation phase here the real implemeation of the slotuin is done we implemet the solution to the given problem by using the geneteic algorithm according to the given problem.

In the given problem a list of 26 items is given they all have different price, different weights and different volumes. The problem says that we have to find the items which can be fitted in to the given space of the container the number of items chosen to be fitted in to the given space should be such that the weight and the volume of the selected items should not be more than the total allowed volume and weight in the container.

The care has to be taken such that the total weight and volume of the selected items should not exceed more than the allowed weight and the volume.

Simmons decision-making model there are four phases

1) Intelligence phase

2) Design phase

3) Choice phase

4) Implementation phase

Initially the problem comes and we are in the intelligence phase thinking of the problem as it comes and then we try to find out what the solution to the given problem and then we move to design phase. In the design phase the way and method to solve the problem is thought and we actually try analyze the problem, we try to find the algorithms and the way that can actually solve the problem and hence we use the genetic algorithm to find the solution to the given problem .After finding the method which is to be applied to the given problem we move to choice phase and here the actual work of finding the best algorithm come .Here we try to find the best algorithm from the given set of algorithm we have the option of choosing the algorithms such as "ACO" algorithm which is called the ant colony optimization algorithm or we have the choice of finding the algorithm such as Simulated annealing (SA) is a related global optimization technique that traverses the search space by testing random mutations on an individual solution. A mutation that increases fitness is always accepted. A mutation that lowers fitness is accepted probabilistically based on the difference in fitness and a decreasing temperature parameter. In SA parlance, one speaks of seeking the lowest energy instead of the maximum fitness. SA can also be used within a standard GA algorithm by starting with a relatively high rate of mutation and decreasing it over time along a given schedule. After deciding that genetic algorithm is the most suitable algorithm for the programming we move to the next step which is the implemetation phase here the real implemeation of the slotuin is done we implemet the solution to the given problem by using the geneteic algorithm according to the given problem.

In the given problem a list of 26 items is given they all have different price, different weights and different volumes. The problem says that we have to find the items which can be fitted in to the given space of the container the number of items chosen to be fitted in to the given space should be such that the weight and the volume of the selected items should not be more than the total allowed volume and weight in the container.

The care has to be taken such that the total weight and volume of the selected items should not exceed more than the allowed weight and the volume.