Range reduction techniques for improving computational efficiency in global optimization of signomial geometric programming problems

2012 ◽  
Vol 216 (1) ◽  
pp. 17-25 ◽  
Author(s):  
Ming-Hua Lin ◽  
Jung-Fa Tsai
Keyword(s):  
Global Optimization ◽  
Computational Efficiency ◽  
Geometric Programming ◽  
Range Reduction ◽  
Reduction Techniques ◽  
Signomial Geometric Programming

scholarly journals A Global Optimization Algorithm for Signomial Geometric Programming Problem

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Xue-Ping Hou ◽  
Pei-Ping Shen ◽  
Yong-Qiang Chen
Keyword(s):  
Linear Programming ◽  
Global Optimization ◽  
Programming Problem ◽  
Optimization Algorithm ◽  
Geometric Programming ◽  
Nonconvex Programming ◽  
Algebraic Manipulation ◽  
Global Optimization Algorithm ◽  
Linear Programming Problems ◽  
Signomial Geometric Programming

This paper presents a global optimization algorithm for solving the signomial geometric programming (SGP) problem. In the algorithm, by the straight forward algebraic manipulation of terms and by utilizing a transformation of variables, the initial nonconvex programming problem (SGP) is first converted into an equivalent monotonic optimization problem and then is reduced to a sequence of linear programming problems, based on the linearizing technique. To improve the computational efficiency of the algorithm, two range reduction operations are combined in the branch and bound procedure. The proposed algorithm is convergent to the global minimum of the (SGP) by means of the subsequent solutions of a series of relaxation linear programming problems. And finally, the numerical results are reported to vindicate the feasibility and effectiveness of the proposed method.

scholarly journals Development of Global Optimization Algorithm for Series-Parallel PHEV Energy Management Strategy Based on Radau Pseudospectral Knotting Method

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3268
Author(s):  
Kegang Zhao ◽  
Jinghao Bei ◽  
Yanwei Liu ◽  
Zhihao Liang
Keyword(s):  
Global Optimization ◽  
Energy Management ◽  
Computational Efficiency ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Minimum Principle ◽  
Management Strategies ◽  
Energy Management Strategy ◽  
Pontryagin Minimum Principle ◽  
Component Sizing

The powertrain model of the series-parallel plug-in hybrid electric vehicles (PHEVs) is more complicated, compared with series PHEVs and parallel PHEVs. Using the traditional dynamic programming (DP) algorithm or Pontryagin minimum principle (PMP) algorithm to solve the global-optimization-based energy management strategies of the series-parallel PHEVs is not ideal, as the solution time is too long or even impossible to solve. Chief engineers of hybrid system urgently require a handy tool to quickly solve global-optimization-based energy management strategies. Therefore, this paper proposed to use the Radau pseudospectral knotting method (RPKM) to solve the global-optimization-based energy management strategy of the series-parallel PHEVs to improve computational efficiency. Simulation results showed that compared with the DP algorithm, the global-optimization-based energy management strategy based on the RPKM improves the computational efficiency by 1806 times with a relative error of only 0.12%. On this basis, a bi-level nested component-sizing method combining the genetic algorithm and RPKM was developed. By applying the global-optimization-based energy management strategy based on RPKM to the actual development, the feasibility and superiority of RPKM applied to the global-optimization-based energy management strategy of the series-parallel PHEVs were further verified.

A fuzzy ranking method with range reduction techniques

2008 ◽  
Vol 184 (3) ◽  
pp. 1032-1043 ◽  
Author(s):  
Li-Ching Ma ◽  
Han-Lin Li
Keyword(s):  
Ranking Method ◽  
Range Reduction ◽  
Reduction Techniques ◽  
Fuzzy Ranking
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