Mixed-Integer Nonlinear Programming (MINLP) is the area of optimization that addresses nonlinear problems with continuous and integer variables. MINLP has proven to be a powerful tool for modeling. At the same time, it combines algorithmic design challenges from combinatorial and nonlinear optimization....
The present work utilizes the DOMINO framework, a data-driven optimization methodology, to address bi-level integrated planning and scheduling problems with mixed-integer nonlinear programming (MINLP) formulations in different multi-product process industries with a high number of variables and constraints...
Such McCormick relaxations provide lower bounds, for example, in branch-and-bound procedures for mixed-integer nonlinear programs but have not gained much attention in PDE-constrained optimization so far. This lack of attention may be due to the distributed nature of such problems, which on the ...
Moreover, also specific techniques from mixed-integer nonlinear programming such as outer approximation (Borrero, Prokopyev, Sauré, 2019, Duran, Grossmann, 1986, Fletcher, Leyffer, 1994) or spatial branching (Horst and Tuy, 2013) are covered; see Belotti et al. (2013); Lee (2012) for ...
편집: John D'Errico 2018년 12월 18일 Not an answer, since I don't have the time right now. But I do recall that only GA does mixed integer nonlinear programming. Since you can always convert a multi-objective problem into a single-objective problem by using a simple linear ...
SHOT is a software for solving mathematical optimization problems of the mixed-integer nonlinear programming (MINLP) class. In addition to MINLP problems, SHOT can also be used for subclasses such as NLP and MI(QC)QP. Originally SHOT was intended for convex MINLP problems only, but as of vers...
The involving nonlinear terms in N-1 constraints are exactly linearized without sacrificing any optimality. Numerical results on two typical integrated energy systems demonstrate the necessity of extending N-1 criterion to the whole network of a combined energy system. Experimental results also show ...
mixed-integer nonlinear programmingglobal optimizationnonconvex constraintsmixed-integer quadratically constrained programmingMINLPMIQCPThis paper describes the extensions that were added to the constraint integer programming framework SCIP in order to enable it to solve convex and nonconvex mixed-integer ...
[28] have introduced a nonlinear programming model and a heuristic algorithm for managing the schedule of a satellite constellation for disaster warning and damage environment analysis. They have prioritized observation tasks over data downloads, and the download policy for onboard memory is ‘first ...
Refs. [30,31] integrate various types of RES resources and use linear and nonlinear programming techniques such as Mixed-Integer Nonlinear Programming (MINLP) and Mixed-Integer Linear Programming (MILP) to derive optimal profits for VPP operators by participating in multiple energy markets. ...