เปรียบเทียบวิธี

	การโปรแกรมจำนวนเต็มผสม	Genetic Algorithm
สาขาวิชา	การจำลอง	การหาค่าเหมาะที่สุด
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	1958–1960	1975
ผู้ริเริ่ม	Ralph Gomory (branch-and-bound cuts, 1958); Land & Doig (branch-and-bound, 1960)	John Henry Holland
ประเภท	Mathematical optimization	Population-based metaheuristic
แหล่งต้นตำรับ	Nemhauser, G. L., Wolsey, L. A. (1988). Integer and Combinatorial Optimization. Wiley-Interscience, New York. ISBN: 9780471359432	Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.
ชื่อเรียกอื่น	MIP, Mixed-Integer Linear Programming, MILP, Integer Programming	GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
ที่เกี่ยวข้อง	6	5
สรุป	Mixed-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.	A genetic algorithm (GA) is a population-based metaheuristic optimization method introduced by John Henry Holland (1975) that mimics the principles of natural selection. It maintains a population of candidate solutions and iteratively improves them through selection, crossover, and mutation operators, making it especially powerful on discontinuous, non-convex, and multi-modal search spaces where classical gradient-based methods fail.