So sánh phương pháp

	Quy hoạch nguyên hỗn hợp đa mục tiêu	Tối ưu hóa đa mục tiêu
Lĩnh vực	Mô phỏng	Mô phỏng
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1980s–2000s	1896 (concept); 1989–2002 (evolutionary algorithms era)
Người khởi xướng	Ehrgott, M.; Mavrotas, G. and others in multi-criteria optimization	Vilfredo Pareto (concept); modern computational formulation by Goldberg and Deb et al.
Loại	Mathematical optimization	Optimization framework
Công trình gốc	Ehrgott, M. (2005). Multicriteria Optimization (2nd ed.). Springer, Berlin. ISBN: 9783540213987	Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester. ISBN: 9780471873396
Tên gọi khác	MO-MIP, Multi-criteria MIP, MOMIP, Multi-objective MILP	MOO, Multi-Criteria Optimization, Vector Optimization, Pareto Optimization
Liên quan	5	3
Tóm tắt	Multi-Objective Mixed-Integer Programming (MO-MIP) is an optimization framework that simultaneously optimizes two or more conflicting objective functions subject to linear or nonlinear constraints, where some decision variables are restricted to integer values and others are continuous. It is widely applied in engineering design, supply chain planning, resource allocation, and scheduling problems that require discrete choices alongside continuous quantities.	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.