Resource Optimization Technique function resources

Due to the campaign structure, the existing decomposition techniques in the SNP optimizer like time decomposition and product decomposition are not applicable. For problems with this structure it is possible to use the resource decomposition in case a good sequence of planning of the campaign resources can be derived. However, in our case, problem instances could be solved without decomposition on a Pentium IV with 2 GHz in one hour to a solution quality of which the objective value deviates at most one percent from the optimal objective function value. 

Linear programming is one of the most common optimization techniques applied. LPs are commonly used on production scheduling and resourcing problems. A linear program is a class of optimization problems where the objective function and constraints are linear. The objective function and constraints of a linear program are convex therefore, a local optimum is the global optimum. In addition, LPs demonstrate the characteristic wherein the optimum solutions of LPs lie on a constraint... 

The increase in computing speed is also making automatic differentiation a powerful resource for nonlinear optimization. In this technique, automatic programs are available that code function derivatives on the basis of a chain-rule application to the elementary constituents of a function. It is foreseeable that such codes will replace finite-difference methods and make Newton methods more powerful. The cost of differentiation is not reduced, but the convenience and accuracy may increase. 

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