quadratic constraint. An optimum solution – optimum point and optimum value – is called Golden if both the slope and the op-timum value constitute the Golden ratio. We show two interesting features. One is the Golden optimum solution. All six problems have the Golden optimum slutions. The other is a cross

of these changes; and therefore, 3) the optimum nutritional and/or financial strategy. It is important to note that optimum solutions are farm-specific and no one solution fits all because of the inherent differences in production characteristics on each farm (e.g health status, genetics, housing, ingredient

The basic issue concerning production in welfare economics is whether a market solution will yield the socially optimum kinds and quantities of commodities. It is well known that problems can arise for three broad reasons: distributive justice; external effects; and scale economies. This paper

advantages include the flexibility of the procedures, as well as the ability to self-adapt the search for optimum solutions on the fly. As desktop computers increase in speed, the application of evolutionary algorithms will become routine. 1 Introduction Darwinian evolution is intrinsically a robust search

During the last decade, the unprecedented increase in the affordable computational power has strongly supported the development of optimization techniques for designing antennas. Among these techniques, genetic algorithm [1] and particle swarm optimization [2] could be mentioned. Most of these techniques use physical dimensions of an antenna

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Consider a convex quadratic program of size L involving m inequality constraints and possibly some equality constraints in n variables. Given a feasible solution whose objective value is within 2^2L of the optimum objective value, we discuss a technique that finds a true optimum solution

description. Optimum energy compaction using Nyquist-M process is presented as a solution for maximi-zing the coding gain of the coder. In two definitions and four theorems the author proves that Nyquist-M filters ful-fill necessary and sufficient conditions imposed on subband signals. Results from Matlab

optimization technique to find the solution to 8 puzzle problem.

the behavior of the BGA for simple test functions. Different mutation schemes are compared by computing the expected progress to the solution. The numerical performance of the BGA is demonstrated on a test suite of multimodal functions. The number of function evaluations needed to locate the optimum scales