Results 241 to 250 of about 131,196 (289)
Some of the next articles are maybe not open access.

Mixed-Integer Linear Programming Formulations

2014
In this chapter, (mixed-)integer linear programming formulations of the resource-constrained project scheduling problem are presented. Standard formulations from the literature and newly proposed formulations are classified according to their size in function of the input data.
Artigues, Christian   +3 more
openaire   +2 more sources

Testing copositivity via mixed–integer linear programming

Linear Algebra and its Applications, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

Nonlinear and Mixed Integer Linear Programming

2012
In this chapter we compare continuous nonlinear optimization with mixed integer optimization of water supply networks by means of a meso scaled network instance. We introduce a heuristic approach, which handles discrete decisions arising in water supply network optimization through penalization using nonlinear programming.
Kolb, Oliver   +3 more
openaire   +2 more sources

Experiments in mixed-integer linear programming

Mathematical Programming, 1971
This paper presents a “branch and bound” method for solving mixed integer linear programming problems. After briefly discussing the bases of the method, new concepts called pseudo-costs and estimations are introduced. Then, the heuristic rules for generating the tree, which are the main features of the method, are presented.
Benichou, M.   +5 more
openaire   +2 more sources

Multiobjective Integer and Mixed-Integer Linear Programming

2016
The introduction of discrete variables into multiobjective programming problems leads to all-integer or mixed-integer problems that are more difficult to tackle, even if they have linear objective functions and constraints. The feasible set is no longer convex, and the additional difficulties go beyond those of changing from single objective linear ...
Carlos Henggeler Antunes   +2 more
openaire   +1 more source

Binary image synthesis using mixed linear integer programming

IEEE Transactions on Image Processing, 1995
Images that are to be transmitted through a distorting imaging system may be deliberately altered to compensate for that distortion. The authors consider an incoherent diffraction-limited imaging system followed by an ideal high-contrast detector that prints binary images, and seek a binary input image (a mask) that generates a desired prescribed ...
Sherif, Sherif   +3 more
openaire   +3 more sources

From Mixed-Integer Linear to Mixed-Integer Bilevel Linear Programming

2017
Bilevel Optimization is a very challenging framework where two players (with different objectives) compete for the definition of the final solution. In this paper we address a generic mixed-integer bilevel linear program, i.e., a bilevel optimization problem where the objective functions and constraints are all linear, and some variables are required ...
openaire   +2 more sources

Mixed-Time Mixed-Integer Linear Programming Scheduling Model

Industrial & Engineering Chemistry Research, 2007
This paper presents a novel mixed-time mixed-integer linear programming (MILP) scheduling model for industrial problems where intermediate storage handling is of particular concern. The proposed model is a crossbreed between a continuous-time and a discrete-time model where a continuous-time representation is incorporated in a discrete-time grid.
Joakim Westerlund   +3 more
openaire   +1 more source

Integer and Mixed Integer Linear Fractional Programming

1997
Some of the problems mentioned in Chapter 1 required that either part of the variables, or all of them take integer values. This chapter will study such problems. In particular, we will address the bivalent programming in which part of the variables or all of them can take only values 0 or 1 (Section 9.1).
openaire   +1 more source

Linear and Mixed Integer Programming

2000
Linear Programming (LP) is one of the most famous optimization techniques introduced independently by Kantarowitsch in 1939 and by Dantzig in 1949 (Kreko, 1973). LP is applicable in decision situations where quantities (variables) can take any real values only restricted by linear (in-) equalities, e. g. for representing capacity constraints. Still, LP
openaire   +1 more source

Home - About - Disclaimer - Privacy