Integer Programming

By George L. Nemhauser, Laurence A. Wolsey. 1972

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Citations in the corpus

Planning and scheduling in the process industry (2002, background): “For the topics of valid inequalities and cutting plane algorithms the reader is referred to the well written book by Wolsey [70].”
Exact Combinatorial Optimization with Graph Convolutional Neural Networks (2019, background): “l optimization. Nonetheless, there exists a broad range of exact combinatorial optimization algorithms, which are guaranteed to ﬁnd an optimal solution despite a worst-case exponential time complexity[49]. An importantpropertyof such algorithmsis that, when interruptedbeforetermination, they can usu”
Subset-Row Inequalities Applied to the Vehicle-Routing Problem with Time Windows (2008, methodology): “The proof follows directly from Chavtal-Gomory’s procedure to construct valid inequalities (Wolsey 1998).”
Hybrid metaheuristics in combinatorial optimization: A survey (2011, unknown): “, [99,100].”
State-of-the-art review of optimization methods for short-term scheduling of batch processes (2006, methodology): “This paper has dealt with MILP methods where the most ommon solution algorithms are LP-based branch and bound ethods (Wolsey, 1998), which are enumeration methods that olve LP subproblems at each node of the search tree (Dakin, 965).”
Bayesian network learning with cutting planes (2011, background): “s asked to look for Gomory cuts. Gomory cuts are general-purpose cutting planes which can be quickly computed from the simplex tableau. For further information on Gomory cuts see, for example, Wolsey [13]. Relying on Gomory cuts alone would be inecient since they are generally not very deep. However”
Mixed Integer Linear Programming Formulation Techniques (2015, methodology): “For more details on basic branch-and-bound and state-of-the-art solvers, we refer the reader to [22, 36, 131, 166] and [1, 2, 25, 23, 92, 112, 24], respectively.”
Reinforcement Learning for Combinatorial Optimization: A Survey (2020, unknown): “al commercial optimizers such as CPLEX [19] or SCIP [20] exist that use branch-and-bound and other routines to solve the mixed-integer linear program. Deﬁnition 2 (Mixed-Integer Linear Program (MILP) [21]). A mixed-integer linear program is an optimization problem of the form argmin x cæx ðAx f b; l”
Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon (2018, background): “Özcan et al. (2012) build a hyper-heuristic for examination timetabling by learning to combine existing heuristics.”