So sánh phương pháp

	Quy hoạch tuyến tính đa mục tiêu (MOLP)	Lập trình mục tiêu	Lập trình tuyến tính	Tối ưu hóa đa mục tiêu
Lĩnh vực	Mô phỏng	Ra quyết định	Tối ưu hóa	Mô phỏng
Họ	Process / pipeline	MCDM	Process / pipeline	Process / pipeline
Năm ra đời	1955–1986	1955	1947	1896 (concept); 1989–2002 (evolutionary algorithms era)
Người khởi xướng	Steuer, R. E.; Charnes, A.; Cooper, W. W.	Charnes, A., Cooper, W. W.	George B. Dantzig	Vilfredo Pareto (concept); modern computational formulation by Goldberg and Deb et al.
Loại	Mathematical optimization / vector optimization	Multi-objective optimisation — weighted/lexicographic goal deviation minimisation	Mathematical programming / continuous optimization	Optimization framework
Công trình gốc	Steuer, R. E. (1986). Multiple Criteria Optimization: Theory, Computation, and Application. John Wiley & Sons, New York. ISBN: 9780471888468	Charnes, A., Cooper, W. W. (1955). Optimal estimation of executive compensation by linear programming. Management Science	Dantzig, G.B. (1963). Linear Programming and Extensions. Princeton University Press. ISBN: 9780691059136	Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester. ISBN: 9780471873396
Tên gọi khác	MOLP, Vector Linear Programming, Multi-criteria LP, Linear Vector Optimization	—	LP, linear optimization, Doğrusal Programlama (LP)	MOO, Multi-Criteria Optimization, Vector Optimization, Pareto Optimization
Liên quan	3	8	4	3
Tóm tắt	Multi-Objective Linear Programming (MOLP) extends classical linear programming to handle several conflicting linear objective functions simultaneously over a feasible region defined by linear constraints. Instead of a single optimal solution, MOLP produces a Pareto-efficient frontier from which a decision-maker selects a preferred trade-off. It is foundational to operations research and management science for resource allocation, planning, and design problems with competing goals.	GOAL-PROGRAMMING (Goal Programming — Minimise deviations from multiple aspiration levels) is a ranking multi-criteria decision-making (MCDM) method introduced by Charnes, A., Cooper, W. W. in 1955. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	Linear programming (LP), pioneered by George B. Dantzig in 1947, is a mathematical method for finding the best value of a linear objective function — such as minimum cost or maximum profit — subject to a set of linear inequality and equality constraints. It is the foundational technique in operations research and underlies production planning, resource allocation, logistics, diet problems, and countless other decision-making scenarios across engineering, economics, and the natural sciences.	Multi-Objective Optimization (MOO) is a mathematical and computational framework for finding solutions that simultaneously optimize two or more conflicting objective functions. Rather than collapsing all goals into a single scalar, MOO produces a set of trade-off solutions — the Pareto front — from which a decision-maker selects according to preference. It is widely used in engineering design, operations research, logistics, economics, and policy analysis.