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Titlebook: Decision Making with Multiple Objectives; Proceedings of the S Yacov Y. Haimes,Vira Chankong Conference proceedings 1985 Springer-Verlag Be

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41#
發(fā)表于 2025-3-28 17:39:05 | 只看該作者
42#
發(fā)表于 2025-3-28 21:30:00 | 只看該作者
Exploiting Resources of a Processor Corete how various options in the method have been implemented. Based on experience to date, it appears that the approach may be a viable alternative for solving multicriteria integer linear programming problems.
43#
發(fā)表于 2025-3-29 00:38:16 | 只看該作者
https://doi.org/10.1007/978-3-031-01858-9organizations interested in applying MOLP; the results have been favorable. These organizations used experimental computer programs that the authors had used in their research and a terse set of instructions to implement the Zionts-Wallenius method.
44#
發(fā)表于 2025-3-29 04:40:37 | 只看該作者
45#
發(fā)表于 2025-3-29 08:26:13 | 只看該作者
46#
發(fā)表于 2025-3-29 13:52:45 | 只看該作者
Multiattribute Utility Analysis and Collective Choice: A Methodological Reviewe decision makers (MDM). Although a main problem of the collective choice is to solve the value conflicts in multiple agents decision making, there will be alternative devices for pretreating diversity of evaluations.
47#
發(fā)表于 2025-3-29 17:28:30 | 只看該作者
Computer Graphics at the Multicriterion Computer/User Interfaceand in evaluating the criterion vector information generated at each iteration. In addition, the paper discusses how interactive computer graphics can be used to modify problem coefficients iteration to iteration in a trajectory optimization context.
48#
發(fā)表于 2025-3-29 20:47:16 | 只看該作者
An Improved Interactive Multicriteria Integer Programming Algorithmte how various options in the method have been implemented. Based on experience to date, it appears that the approach may be a viable alternative for solving multicriteria integer linear programming problems.
49#
發(fā)表于 2025-3-30 00:41:45 | 只看該作者
50#
發(fā)表于 2025-3-30 06:46:00 | 只看該作者
Databases and Information Systemsderived from the SMC. In this case an efficient solution is found with the aid of goal programming models. These models are analysed with respect to convexity properties of the objective function, considering normal or uniform distribution.
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