পদ্ধতির তুলনা করুন

	সীমাবদ্ধতা প্রোগ্রামিং	ডায়নামিক প্রোগ্রামিং	রৈখিক প্রোগ্রামিং
ক্ষেত্র	অনুকূলকরণ	অনুকূলকরণ	অনুকূলকরণ
পরিবার	Process / pipeline	Process / pipeline	Process / pipeline
উদ্ভবের বছর	2006	1957	1947
প্রবর্তক	Rossi, van Beek & Walsh	Richard Bellman	George B. Dantzig
ধরন	Declarative combinatorial optimization	Exact combinatorial optimization via recursive decomposition	Mathematical programming / continuous optimization
মৌলিক উৎস	Rossi, F., van Beek, P., & Walsh, T. (Eds.). (2006). Handbook of Constraint Programming. Elsevier. ISBN: 978-0-444-52726-4	Bellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6	Dantzig, G.B. (1963). Linear Programming and Extensions. Princeton University Press. ISBN: 9780691059136
অপর নাম	Constraint Satisfaction Programming, Constraint-Based Optimization, Kısıt Programlama, CSP Optimization	DP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik Programlama	LP, linear optimization, Doğrusal Programlama (LP)
সম্পর্কিত	3	3	4
সারসংক্ষেপ	Constraint Programming (CP) is a declarative optimization paradigm in which a problem is formulated as a set of variables, finite domains, and constraints, and a solver systematically searches for assignments that satisfy all constraints. Formalized comprehensively by Rossi, van Beek, and Walsh in their 2006 Handbook of Constraint Programming, CP unifies propagation-based pruning with intelligent backtracking search to tackle combinatorial problems across scheduling, planning, and configuration domains.	Dynamic Programming (DP) is an exact optimization technique introduced by Richard Bellman in 1957 for solving multi-stage decision problems. It decomposes a complex problem into simpler, overlapping subproblems, solves each subproblem once, and stores the results to avoid redundant computation. Grounded in the Principle of Optimality, DP guarantees globally optimal solutions whenever the problem exhibits overlapping subproblems and optimal substructure.	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.