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Combinatorial Optimization: Algorithms and Complexity Christos H. Papadimitriou, Kenneth Steiglitz
Publisher: Dover Publications

Since ATSP instances are more complex, in many cases, ATSP instances are transformed into STSP instances and subsequently solved using STSP algorithms [4]. Combinatorial Optimization: Algorithms and Complexity (Dover Books on Computer Science). Data Structures and Algorithms. Due to the NP completeness of many combinatorial optimization problems, they are quite difficult to be solved analytically, and exact search algorithms such as branch and bound may degenerate to complete enumeration, and the CPU time needed to solve them may grow exponentially in the worst case. Combinatorial Optimization - Algorithms and Complexity. Combinatorial Optimization: Algorithms and Complexity. An Introduction to the Theory of Numbers. However, in the present study we solve the ATSP instances without transforming into STSP instances. The TSP is a NP-complete combinatorial optimization problem [3]; and roughly speaking it means, solving instances with a large number of nodes is very difficult, if not impossible. Among these patterns, the real encoding has been shown to have more capability for complex problems (Andrzej [26]). Introduction to Algorithms: A Creative Approach.