 Author Topic: Resource Allocation Using Genetic Algorithms  (Read 2390 times)

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• Research Paper Publishing Resource Allocation Using Genetic Algorithms
« on: January 22, 2011, 05:54:24 am »
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Author : S. Ranichandra, T. K. P. Rajagopal
International Journal of Scientific & Engineering Research, Volume 1, Issue 2, November-2010
ISSN 2229-5518

Many business and economic situations are concerned with a problem of planning activity. In each case, there are limited resources at the disposal and the problem is to make use of these resources so as to yield the maximum production or to minimize the cost of production, or to give the maximum profit, etc. Such problems are referred to as the problems of constrained optimization.

LPP is a technique for determining an optimum schedule of interdependent activity in view of the available resources. The term "programming" means "planning" which refers to the process of determining a particular plan of action from amongst several alternatives. The general form of a LPP is described as follows. Let z be a linear function on Rn defined by
z = c1x1 + C2X2 + .. . + cnxn                      (a)
where cjs are constants. Let (aij) be an m x n real matrix and let {b1,b2.. . bm} be a set of constants such that
a11X1 + a12X2 +.... + a1nXn>= or<=or = or> or<b1
a21X1 + a22X2 + ... + a2nXn >= or<=or = or> or<b2
am1x1 + am2X2 + . . . + amnxn >= or<=or = or> or<bm

and finally let
Xj>=0;j = l,2,3,...n                  (c)

The problem of determining an n-tuple (x1, x2, . . . xn) which makes z a minimum (or maximum) and which satisfies (b) and (c) is called the general LPP.

The objective of the GAs is to find an optimal solution to a problem. Of course, since GAs is heuristic procedures, they are able to find very good solutions for a wide range of problems. GAs work by evolving a population of individuals over a number of generations. A fitness value is assigned to each individual in the population, where the fitness computation depends on the application.

The main advantages of Genetic Algorithms are: