نتایج جستجو برای: mixed integer nonlinear programming
تعداد نتایج: 770161 فیلتر نتایج به سال:
A Unifying Framework for the Convexification of Mixed-Integer Conic Binary Sets The paper “Conic Mixed-Binary Sets: Convex Hull Characterizations and Applications,” by Fatma Kilinc-Karzan, Simge Kucukyavuz, Dabeen Lee, Soroosh Shafieezadeh-Abadeh, develops a unifying framework convexifying mixed-integer conic binary sets. Many applications in machine-learning operations research give rise to in...
a modified method to determine a well-dispersed subset of non-dominated vectors of an momilp problem
this paper uses the l1−norm and the concept of the non-dominated vector, topropose a method to find a well-dispersed subset of non-dominated (wdsnd) vectorsof a multi-objective mixed integer linear programming (momilp) problem.the proposed method generalizes the proposed approach by tohidi and razavyan[tohidi g., s. razavyan (2014), determining a well-dispersed subset of non-dominatedvectors of...
The separation of solid particles from gas-solid process streams is an important unit operation in many chemical processes. Out the different types equipment that are used for separation, cyclone separators widely their operational flexibility, efficiency and capital cost. This study focused on design optimal configuration several cyclones a fertilizer plant. granulation step plant leads to usi...
The decomposition-based outer approximation algorithm for convex mixed-integer nonlinear programming
We propose a modified sequential quadratic programming (SQP) method for solving mixed-integer nonlinear programming problems. Under the assumption that integer variables have a smooth influence on the model functions, i.e., that function values do not change drastically when inor decrementing an integer value, successive quadratic approximations are applied. The algorithm is stabilized by a tru...
We propose an exact penalty approach for solving mixed integer nonlinear programming (MINLP) problems by converting a general MINLP problem to a finite sequence of nonlinear programming (NLP) problems with only continuous variables. We express conditions of exactness for MINLP problems and show how the exact penalty approach can be extended to constrained problems.
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