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) ...
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 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...
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...
如果票数必须是整数，则需要mixed-integer nonlinear programming。如果不要求整数，则非线性优化大概可以...
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 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 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...
The Sequential Mixed Integer Nonlinear Programming (SMINLP) optimizer is equivalent to the SNLP optimizer with only one difference. Many problems require variables take only discrete values. One example might be to optimize on the number of turns in a coil. To be able to optimize on number of...