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Целочислено линейно оптимиране×Метод на разклонение и граница×
ОбластСимулационно моделиранеОптимизация
СемействоProcess / pipelineProcess / pipeline
Година на възникване1958–19601960
СъздателRalph Gomory (branch-and-bound cuts, 1958); Land & Doig (branch-and-bound, 1960)Ailsa Land & Alison Doig
ТипMathematical optimizationExact combinatorial optimization algorithm
Основополагащ източникNemhauser, 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 ↗
Други названияMIP, Mixed-Integer Linear Programming, MILP, Integer ProgrammingB&B, Land-Doig Algorithm, Implicit Enumeration, Dal ve Sınır
Свързани63
РезюмеMixed-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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  2. 2 Източници
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ScholarGateСравнение на методи: Mixed-Integer Programming · Branch and Bound. Извлечено на 2026-06-15 от https://scholargate.app/bg/compare