Solving Of Linear Programming Problems Research Articles

Semiotic analysis of formal operational students with field dependent and field independent cognitive style in linear programming problem solving

Tujuan penelitian ini adalah untuk mendeskripsikan semiotika siswa operasional formal dengan gaya kognitif berbeda dalam pemecahan masalah pemrograman linear. Subjek penelitian ini adalah satu siswa bergaya kognitif field-dependent (SFD) dan satu siswa bergaya kognitif field-independent (SFI). Data penelitian ini dikumpulkan melalui pemberian tugas pemecahan masalah pemrograman linear dan wawancara semi-terstruktur berbasis tugas. Proses analisis jawaban siswa dalam pemecahan masalah pemrograman linear berdasarkan indikator semiotika yang meliputi simbol, kode, dan makna serta tahapan pemecahan masalah Polya. Hasil analisis data menunjukkan bahwa semiotika yang dilakukan kedua siswa operasional formal dengan gaya kognitif berbeda ini dalam memecahkan masalah pemrograman linear belum menciptakan informasi yang bermakna karena pada penggunaan simbol, pembuatan kode, dan pembuatan makna tidak dilakukan secara lengkap.

Technological Safety and the Production System

Implementation of disease detection systems and technology safety management in the states is intended. The technique of defining the security center based on the linear programming problem solving and two-level system decisionmaking on technology safety assurance is presented. In the first level the safety center is defined, in the second level the process stability problem in the field of safe operation is solved.

Risk optimization with p-order conic constraints: A linear programming approach

The paper considers solving of linear programming problems with p-order conic constraints that are related to a certain class of stochastic optimization models with risk objective or constraints. The proposed approach is based on construction of polyhedral approximations for p-order cones, and then invoking a Benders decomposition scheme that allows for efficient solving of the approximating problems. The conducted case study of portfolio optimization with p-order conic constraints demonstrates that the developed computational techniques compare favorably against a number of benchmark methods, including second-order conic programming methods.

Switched-capacitor neural networks for linear programming

A circuit for online solving of linear programming problems is presented. The circuit uses switched-capacitor techniques and is thus suitable for monolithic implementation. The connection of the proposed circuit to analogue neural networks is also outlined. >