Handbook of combinatorial optimization. 1
The first of a multi-volume set, which deals with several algorithmic approaches for discrete problems as well as many combinatorial problems. It is addressed to researchers in discrete optimization, and to all scientists who use combinatorial optimization methods to model and solve problems.
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Approximate Algorithms and Heuristics for MAXSAT
Connections between Nonlinear Programming
Interior Point Methods for Combinatorial Optimization
Fractional Combinatorial Optimization
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algorithm applications approach approximation arcs assignment assume binary branching called clauses combinatorial optimization complexity Computer consider constraints continuous convex corresponding cost Covering cutting cutting plane defined derived direction Discrete dynamic edge equal equivalent example exists factors feasible fixed flow formulation fractional function given global graph Heuristic implies improved inequalities instances integer programming interior point iterations Journal Knapsack Problem linear programming Location lower bound Mathematical maximize maximum method minimal multipliers node Note objective obtained Operations Research optimal solution otherwise path performance plane polynomial possible presented primal Proof properties reduced relaxation respect Routing satisfied Scheduling semidefinite programming solution solved Step structure techniques Theorem tion Transportation upper bound variables vector Vehicle weight