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Combinatorial optimization intersects operations research, computer science, and applied mathematics, addressing problems in diverse fields like network design, scheduling, and computational biology. It involves the mathematical formulation of problems for minimization or maximization, emphasizing the commonality of discreteness. The discipline evolved from linear programming, which has numerous applications, and was influenced by significant discoveries like the ellipsoid method and interior point approaches, leading to polynomial-time algorithms that impact both linear programming and NP-hard problem-solving.
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Handbook of Combinatorial Optimization, Dingzhu Du, Panos M. Pardalos
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- 2011
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