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Mješovito cjelobrojno programiranje×Podjela i omeđivanje (Branch and Bound)×
PodručjeSimulacijaOptimizacija
ObiteljProcess / pipelineProcess / pipeline
Godina nastanka1958–19601960
TvoracRalph Gomory (branch-and-bound cuts, 1958); Land & Doig (branch-and-bound, 1960)Ailsa Land & Alison Doig
VrstaMathematical optimizationExact combinatorial optimization algorithm
Temeljni izvorNemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. Wiley-Interscience, New York. ISBN: 9780471359432Land, A. H., & Doig, A. G. (1960). An automatic method of solving discrete programming problems. Econometrica, 28(3), 497–520. DOI ↗
Drugi naziviMIP, Mixed-Integer Linear Programming, MILP, Integer ProgrammingB&B, Land-Doig Algorithm, Implicit Enumeration, Dal ve Sınır
Srodne63
SažetakMixed-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.Branch and Bound is a systematic exact algorithm for combinatorial and integer optimization problems, introduced by Ailsa Land and Alison Doig in 1960. It organizes the search space as a tree of subproblems, uses relaxation-derived upper bounds to prune branches that cannot improve the best known solution, and guarantees finding a globally optimal integer solution. It is the backbone of modern mixed-integer programming solvers used in operations research, logistics, scheduling, and engineering design.
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ScholarGateUsporedite metode: Mixed-Integer Programming · Branch and Bound. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare