Mark Ugo Department of Statistics, School of ICT. Federal Polytechnic Auchi, Edo State.
Abstract.
In our production sectors, the knowledge of optimization problems is paramount and cannot be over emphasized. It is one of the bed rocks for manufacturers and decision makers in various fields of discipline to make accurate and precise judgment on real world problems that can be recast as optimization problem. To achieve such laudable objectives, various methodologies have been adopted and applied, hence this research work. In this research work, one of the methods adopted is the application of the Lagrangean function that satisfied Kuhn and Tucker conditions on the real world problems extracted from Ovason Molding Company. The problem as extracted from the company is a Non-Linear Constrained Optimization Problems that is based on finite 4 dimensional space in . In this problem, we specifically examined ?Impact of R Convexity? on the cost minimization problem of the company in producing at least one low tension (LT) of concrete electric pole and hence applied the Lagrangean function that satisfied Kuhn and Tucker conditions for optimal solution. The solution obtained is based on characterization (continuity and differentiability) of convex and concave functions. From our findings it is discovered that the result of the problem actually depicts reduction in price for producing one low tension (LT) of concrete electric pole, as against the market price of the company. The result of the problem indeed stands to correct among other things wrong impressions created by the manager of the company about prices of such commodity.
keywords: Convexity, non-linear constrained optimization.