Bi-level optimization based on fuzzy if-then rule

A bi-level programming problem has been developed where the functional relationship linking decision variables and the objective functions of leader and follower are not utterly well known to us. Because of the uncertainty in practical life decision-making situation most of the time it is inconvenient to find the veracious relationship between the objective functions of leader, follower and the decision variables. It is expected that the source of information which gives some command about the objective functions of leader and follower, is composed by a block of fuzzy if-then rules. In order to analyze the model, A dynamic programming approach with a suitable fuzzy reasoning scheme is applied to calculate the deterministic functional relationship linking the decision variables and the objective functions of leader as well as follower. Thus a bi-level programming problem is constructed from the actual fuzzy rule-based to the conventional bi-level programming problem. To solve the final problem, we use the lingo software to find the optimal of objective function of follower first and using its solution we optimize the objective function of leader. A numerical example has been solved to signify the computational procedure.</p

Penilaian Prestasi Kinerja Pegawai Menggunakan Fuzzy Tsukamoto

Pengukuran kinerja pegawai pada suatu perusahaan merupakan hal yang sangat penting untuk evaluasi dan perencanaan perusahaan di masa datang. Setiap perusahaan  mempunyai  cara  yang  berbeda  dalam  melakukan  penilaian  kinerja  pegawai. Penilaian  kinerja harus dilakukan  dengan metode yang baik dan tepat sehingga dapat menjamin perlakuan yang adil serta memuaskan bagi para pegawai yang dinilai. Hal ini dapat menumbuhkan loyalitas dan semangat kerja pegawai. Pada makalah ini dibahas pembuatan sistem penilaian kinerja pegawai menggunakan Sistem Inferensi Fuzzy Tsukamoto. Parameter yang digunakan untuk batasan fungsi keanggotaan fuzzy berdasarkan pendapat pakar yaitu tanggung jawab, kedisiplinan dan faktor pengurang. Akurasi sistem dihitung dengan membandingkan keluaran sistem dengan penilaian pakar. Hasil uji coba menunjukkan bahwa sistem yang dibangun menghasilkan akurasi 84%