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Impact Analysis of the Market Penetration Rate of Connected Vehicles and the Failure Rate of Roadside Equipment on Data Accuracy. [PDF]
Sensors (Basel)Zhan F.
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Mixed-Integer Linear Programming Formulations
2014In 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
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Site Location via Mixed-Integer Programming
Operational Research Quarterly (1970-1977), 1972It 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.
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Mixed Integer Programming Computation
2009The 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 ...
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Presolve Reductions in Mixed Integer Programming
INFORMS Journal on Computing, 2020Mixed integer programming has become a very powerful tool for modeling and solving real-world planning and scheduling problems, with the breadth of applications appearing to be almost unlimited. A critical component in the solution of these mixed integer programs is a set of routines commonly referred to as presolve.
Tobias Achterberg +4 more
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Stochastic Mixed-Integer Programming
2019In 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 +2 more
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Integer and Mixed-Integer Programming
1997We survey techniques for sensitivity analysis of integer programming and related problems. The emphasis is on finding analogues from linear programming.
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Structure Detection in Mixed-Integer Programs
INFORMS Journal on Computing, 2018Despite 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 +2 more
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Exact mixed-integer programming
2020In 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.
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Mixed-integer quadratic programming
Mathematical Programming, 1982This paper considers mixed-integer quadratic programs in which the objective function is quadratic in the integer and in the continuous variables, and the constraints are linear in the variables of both types. The generalized Benders' decomposition is a suitable approach for solving such programs.
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