Results 261 to 270 of about 363,713 (312)

Machine Learning Augmented Branch and Bound for Mixed Integer Linear Programming

Mathematical programming
Mixed Integer Linear Programming (MILP) is a pillar of mathematical optimization that offers a powerful modeling language for a wide range of applications. The main engine for solving MILPs is the branch-and-bound algorithm.
Lara Scavuzzo, K. Aardal, Andrea Lodi, Neil Yorke-Smith   +3 more
semanticscholar   +1 more source

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, Kone, Oumar, Lopez, Pierre, Mongeau, Marcel   +3 more
openaire   +2 more sources

Flexible Assembly Job-Shop Scheduling With Sequence-Dependent Setup Times and Part Sharing in a Dynamic Environment: Constraint Programming Model, Mixed-Integer Programming Model, and Dispatching Rules

IEEE transactions on engineering management, 2018
This paper studies the flexible assembly job-shop scheduling problem in a dynamic manufacturing environment, which is an exension of job-shop scheduling with incorporation of serveral types of flexibilies and integration of an assembly stage.
Sicheng Zhang, Shouyang Wang
semanticscholar   +1 more source

Site Location via Mixed-Integer Programming

Operational Research Quarterly (1970-1977), 1972
It is demonstrated that mixed-integer programming can be applied successfully to the solution of certain practical site location problems. A mixed-integer model of a frequently occurring form of warehouse location problem is presented. Experience with models of this type is described with examples of computational performance.
openaire   +2 more sources

Stochastic Mixed-Integer Programming

2019
In this chapter we consider a generalization of the recourse model in Chap. 3, obtained by allowing integrality restrictions on some or all of the decision variables. First we give some motivation why such mixed-integer recourse models are useful and interesting. Following the presentation of the general model, we give several examples of applications.
Willem K. Klein Haneveld, Maarten H. van der Vlerk, Ward Romeijnders   +2 more
openaire   +1 more source

A mixed integer programming approach to the tensor complementarity problem

Journal of Global Optimization, 2018
The tensor complementarity problem is a special instance of nonlinear complementarity problems, which has many applications. How to solve the tensor complementarity problem, via analyzing the structure of the related tensor, is one of very important ...
S. Du, Liping Zhang
semanticscholar   +1 more source

Structure Detection in Mixed-Integer Programs

INFORMS Journal on Computing, 2018
Despite vast improvements in computational power, many large-scale optimization problems involving integer variables remain difficult to solve. Certain classes, however, can be efficiently solved by exploiting special structure. One such structure is the singly bordered block-diagonal (BBD) structure that lends itself to Dantzig-Wolfe decomposition ...
Taghi Khaniyev, Samir Elhedhli, Fatih Safa Erenay   +2 more
openaire   +1 more source

Mixed Integer Programming Computation

2009
The first 50 years of Integer and Mixed-Integer Programming have taken us to a very stable paradigm for solving problems in a reliable and effective way. We run over these 50 exciting years by showing some crucial milestones and we highlight the building blocks that are making nowadays solvers effective from both a performance and an application ...
openaire   +3 more sources

Multi-objective mixed integer programming and an application in a pharmaceutical supply chain

International Journal of Production Research, 2018
Multi-objective integer linear and/or mixed integer linear programming (MOILP/MOMILP) are very useful for many areas of application as any model that incorporates discrete phenomena requires the consideration of integer variables.
S. Singh, M. Goh
semanticscholar   +1 more source

Exact mixed-integer programming

2020
In this thesis, we develop and implement an efficient algorithm that can exactly solve instances of the mixed-integer programming problem that are given by rational data. For a feasible instance, a truly optimal solution will be computed; for an infeasible instance, a provably correct infeasibility certificate will be issued.
openaire   +1 more source