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Mixed-Integer Programming

Mixed-Integer Programming (MIP) is a mathematical optimization framework in which some decision variables must take integer values while others may be continuous. It generalizes linear programming and is widely used in operations research, logistics, scheduling, resource allocation, and engineering design, where indivisibility constraints — such as yes/no decisions or whole-unit quantities — arise naturally.

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Mixed-Integer Programming (MIP) — Mathematical optimization with continuous and integer decision variables

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Nemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. Wiley-Interscience, New York. · ISBN 9780471359432
Wolsey, L. A. (1998). Integer Programming. Wiley-Interscience, New York. · ISBN 9780471283669

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Same method familyBranch and Boundmachine-suggested · Relational suggestion, not evidence.Same method familyDynamic Programmingmachine-suggested · Relational suggestion, not evidence.Same method familyGenetic Algorithmmachine-suggested · Relational suggestion, not evidence.Same method familyLinear Programmingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-objective mixed-integer programmingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketStochastic Mixed-Integer Programmingmachine-suggested · Relational suggestion, not evidence.