A General Model of Some Inverse Combinatorial Optimization Problems and Its Solution Method Under l ∞ Norm
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DOI: 10.1023/A:1013807829021
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- Nimrod Megiddo, 1979. "Combinatorial Optimization with Rational Objective Functions," Mathematics of Operations Research, INFORMS, vol. 4(4), pages 414-424, November.
- Zhang, Jianzhong & Liu, Zhenhong & Ma, Zhongfan, 2000. "Some reverse location problems," European Journal of Operational Research, Elsevier, vol. 124(1), pages 77-88, July.
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- Libura, Marek, 2007. "On the adjustment problem for linear programs," European Journal of Operational Research, Elsevier, vol. 183(1), pages 125-134, November.
- Çiğdem Güler & Horst W. Hamacher, 2010. "Capacity inverse minimum cost flow problem," Journal of Combinatorial Optimization, Springer, vol. 19(1), pages 43-59, January.
- Yong He & Binwu Zhang & Enyu Yao, 2005. "Weighted Inverse Minimum Spanning Tree Problems Under Hamming Distance," Journal of Combinatorial Optimization, Springer, vol. 9(1), pages 91-100, February.
- Xiucui Guan & Panos Pardalos & Xia Zuo, 2015. "Inverse Max + Sum spanning tree problem by modifying the sum-cost vector under weighted $$l_\infty $$ l ∞ Norm," Journal of Global Optimization, Springer, vol. 61(1), pages 165-182, January.
- Junhua Jia & Xiucui Guan & Qiao Zhang & Xinqiang Qian & Panos M. Pardalos, 2022. "Inverse max+sum spanning tree problem under weighted $$l_{\infty }$$ l ∞ norm by modifying max-weight vector," Journal of Global Optimization, Springer, vol. 84(3), pages 715-738, November.
- Abd Allah A. Mousa & Yousria Abo-Elnaga, 2020. "Stability of Solutions for Parametric Inverse Nonlinear Cost Transportation Problem," Mathematics, MDPI, vol. 8(11), pages 1-21, November.
- Egri, Péter & Kis, Tamás & Kovács, András & Váncza, József, 2014. "An inverse economic lot-sizing approach to eliciting supplier cost parameters," International Journal of Production Economics, Elsevier, vol. 149(C), pages 80-88.
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Keywords
path; cycle; mean-cycle; assignment; spanning tree; matching; matroid intersection; basis;All these keywords.
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