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A. Thapar and D. Pandey, et al., “Satisficing solutions of multi-objective fuzzy optimization problems using genetic algorithm,” Applied Soft Computing, Vol. 12, No. 8, 2012, pp. 2178-2187.

has been cited by the following article:

• TITLE: Multi-Objective Optimization of Pilots’ FFS Recurrent Training Problem

  AUTHORS: Mingang Gao

  KEYWORDS: PFRT Problem; Multi-Objective Programming; Bipartite Graph; Longest-Route Problem; Graphic Method

  JOURNAL NAME: Engineering, Vol.4 No.10, October 11, 2012

  ABSTRACT: Two multi-objective programming models are built to describe Pilots’ full flight simulator (FFS) recurrent training (PFRT) problem. There are two objectives for them. One is the best matching of captains and copilots in the same aircraft type. The other is that pilots could attend his training courses at proper month. Usually the two objectives are conflicting because there are copilots who will promote to captains or transfer to other aircraft type and new trainees will enter the company every year. The main theme in the research is to find the final non-inferior solutions of PFRT problem. Graph models are built to help to analyze the problem and we convert the original problem into a longest-route problem with weighted paths. An algorithm is designed with which we can obtain all the non-inferior solutions by a graphic method. A case study is present to demonstrate the effectiveness of the algorithm as well.