Learn how to use dynamic programming for multiple objectives, such as cost, quality, profit, and risk. Find out the concept, methods, advantages, and examples of this technique.

However, traditional dominace-relation based multi-objective genetic programming algorithms are limited to biasing easily to small and ineffective scheduling heuristics. This paper presents a ...

Abstract: This paper presents a hybrid programming framework for solving multi-objective optimization problems in supply chain. The proposed approach consists of the integration and hybridization of ...

M. Sun, “Some issues in measuring and reporting solu-tion quality of interactive multiple objective programming procedures,” European Journal of Operational Research, Vol. 162, pp. 468–483, 2005. M.

4. Synthesis and applications. The multi-objective optimization program presented can be adapted to other environmental management problems, and easily incorporates a wide range of quantifiable ...

Then, a multi-objective reactive power optimization model is established to minimize the power generation cost of conventional units, the penalty cost of wind and ... This research was funded by the ...