J.N. Hooker, Logic-based methods for optimization: combining optimization and con- straint satisfaction. John Wiley Sons, 2000. - 495 pp.Hooker, J.N.: `Logic-based methods for optimization: combining optimization and constraint satisfaction' (Wiley, 2000)...
MINLP: logic-based methods - Grossmann () Citation Context ... a general LPCC, without any assumption on the problem. In turn, the key idea behind this algorithm is closely related to the logic-based Benders decomposition for solving linear disjunctive programs =-=[7,13,19,17,18]-=-. ...
N., Logic-based methods for optimization, in A. Borning, ed., Principles and Practice of Constraint Programming, Lecture Notes in Computer Science 874 (1994) 336-349. 13] Hooker, J. N. and C. Fedjki, Branch-and-cut solution of inference problems in propositional logic, Annals of ...
In an article (Grossmann and Biegler, 2004) on the future perspective of optimization, logic based methods such as disjunctive programming and CP have been identified as promising techniques for efficiently solving discrete optimization problems. CP has found applications in diverse areas and has ...
optimization methods, 40 independent optimization runs are conducted to determine the statistical measurements as the mean, standard deviation, and the required number of objective function evaluations. A predetermined stopping criterion is also taken into consideration, which is based on a tolerance of ...
▶ The Fuzzy function is decided based on power loss and voltage. ▶ This optimization tool has used to reduce the cost of peak power and energy loss. ▶ The efficacy of the method is validated by defining two scenarios for power system....
program and model manipulation AI methods for program development verification and testing of AI-based systems transformational techniques in software engineering logic-based methods for security logic-based methods for cyber-physical and distributed systems applications, tools, and industrial practice Survey ...
Some of these methods are based on the assignment of scores, noted as (pk), to the selection criteria, cj , of assets, so that the decision-making problem for asset selection is based on identifying those asset classes that satisfy the max condition max ∑nj=1 cj × pj . Regardless of...
not uncertainty in the probabilistic sense. Membership in a fuzzy set is usually represented graphically. Membership functions are determined by both theoretical andempiricalmethods that depend on the particular application, and they may include the use of learning and optimization techniques such asneural...
Agent-Based System Dynamics The three methods can be used in any combination, with one software, to simulate business systems of any complexity. In AnyLogic simulation software, you can use various visual modeling languages: process flowcharts, statecharts, action charts, and stock & flow diagrams...