A wide range of nonlinear optimization problems involve integer or discrete variables in addition to the continuous variables. These classes of optimization problems arise from a variety of applications and are denoted as mixed integer nonlinear programming MINLP problems. The integer variables can be ...
Mixed integer programming problems are defined as those where some or all of the decision variables are only allowed to be integers. This is typically required in a range of real world applications in allocation and planning problems where the discrete variables represent quantities, such as the nu...
Mixed Integer Nonlinear ProgrammingSebastian SagerDiscrete Optimization GroupInstitute for Computer ScienceUniversity of HeidelbergWorkshop Mixed Integer ProgrammingFebruary 16 – 18, 2005Heidelberg 阅读了该文档的用户还阅读了这些文档 1 p. 安全生产责任考核制度 3 p. 安全检查管理制度 6 p. 安全教育管理...
Mixed-Integer Nonlinear ProgrammingMichael R. Bussieck Armin Pruessner ∗February 19, 2003AbstractRecently, the area of Mixed Integer Nonlinear Programming (MINLP)has experienced tremendous growth and a flourish of research activity.In this article we will give a brief overview of past developments in...
The solverecpMINLPsolves convex or pseudo-convex mixed-integer nonlinear programming problems using an extended cutting plane algorithm with cuts regulated by a parameter-vector alpha. Cuts and linearizations are added to MIP subproblem which is then solved by a subsolver in each iteration. ...
The filterSQP solver is a Sequential Quadratic Programming solver suitable for solving large, sparse or dense linear, quadratic and nonlinear programming problems. The method avoids the use of penalty functions. Global convergence is enforced through the use of a trust--region and the new concept ...
mixed-integer nonlinear programming Runhong Qi 1 , Michael A. Henson * Department of Chemical Engineering, Louisiana State Uni6ersity, Baton Rouge, LA 70803-7303, USA Received 4 April 1999; received in revised form 24 August 2000; accepted 24 August 2000 Abstract An optimal design strategy for...
The MISQP solver handles dense mixed-integer nonlinear programming problems by a modified sequential quadratic programming (SQP) method. Under the assumption that integer variables have a smooth influence on the model functions, i.e., that function values do not change drastically when in- or decre...
Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problem...
6 Mixed Integer Nonlinear Programming Applications uses explicitly the feature that production equals the capacity rates in order to compute a priori the number of periods to produce a cam- paign of specified minimal size. If daily production can take any value between zero and the capacity rat...