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Lập trình nguyên (Integer Programming×Simheuristics: Kết hợp mô phỏng với siêu heuristic để tối ưu hóa ngẫu nhiên×
Lĩnh vựcTối ưu hóaTối ưu hóa
HọProcess / pipelineProcess / pipeline
Năm ra đời19582015
Người khởi xướngRalph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960)Juan et al.
LoạiMathematical optimisation — exact combinatorial methodHybrid simulation-optimization framework
Công trình gốcWolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669Juan, A. A., et al. (2015). A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems. Operations Research Perspectives, 2, 62–72. DOI ↗
Tên gọi khácIP, MIP, mixed-integer programming, mixed-integer linear programmingSimulation-based Metaheuristics, Stochastic Metaheuristics with Simulation, Hybrid Simulation-Optimization, Simülistik Sezgiseller
Liên quan43
Tóm tắtInteger programming (IP), also called mixed-integer programming (MIP) when only some variables are restricted to whole numbers, is a branch of mathematical optimisation in which some or all decision variables must take integer or binary values. Building on linear programming, it was formalised through Ralph Gomory's cutting-plane method (1958) and the Land-and-Doig branch-and-bound algorithm (1960), and it has since become the standard exact framework for scheduling, assignment, routing, and resource-allocation problems.Simheuristics is a hybrid algorithmic framework that integrates Monte Carlo or discrete-event simulation into metaheuristic search procedures to solve stochastic combinatorial optimization problems. Introduced by Juan et al. in 2015, it addresses settings where objective function evaluations involve random variables, providing near-optimal solutions with probabilistic quality guarantees. The approach is especially suited for real-world logistics, transportation, and scheduling problems where uncertainty is inherent and classical deterministic solvers fail to capture variability.
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