This paper proposes a logicbased approach to optimization that combines solution methods from mathematical programming and logic programming. Global optimization methods can generally be classified as stochastic and deterministic. This approach can combine some of the problemsolving wisdom accumulated by mathematical programmers with techniques and insights from constraint pro. Optimization methods are somewhat generic in nature in that many methods work for wide variety of problems. The techniques are classified as either local typically gradientbased or global typically nongradient based or evolutionary.
It is conceivable that portions of both will merge into a. Future perspective on optimization ignacio grossmann. Optimization methods in 1122012 dsp 26 class algorithm function q q comp. Lagrangian methods general formulation of constrained problems. Optimization, constraint programming, logicbased methods, artificial intelligence. Interpretation of lagrange multipliers as shadow prices. Logic, optimization and constraint programming carnegie mellon.
Yet no generally accepted principle or scheme for their merger has evolved. A pioneering look at the fundamental role of logic in optimization and constraint satisfaction. Optimization of inventory strategies to enhance customer service, reduce lead times and costs and meet market demand 3, 15. Pdf logicbased methods for optimization researchgate. We also indicate how semantic query optimization techniques can be extended to databases. The purpose of the following sections is to exhibit optimization algorithms that can be used for multiplequery optimization either as plan mergers or as global optimizers. Pdf this paper proposes a logicbased approach to optimization that combines.
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