A Two-Stage Filter Split-Optimization Approach for Obtaining Multiple Solutions with Identical Objective Value
| Autor: | Pan Zou, Hungyi Chen, Steven Y. Liang, Chiu-Feng Lin, Zhi-Wen Fan, Manik Rajora, Mingyou Ma, Ying-Cheng Lu, Wen Chieh Wu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Work (thermodynamics) Mathematical optimization Control and Optimization Optimization problem Computer science lcsh:Mechanical engineering and machinery Value (computer science) 02 engineering and technology Process variable Industrial and Manufacturing Engineering 020901 industrial engineering & automation two-stage filter 0202 electrical engineering electronic engineering information engineering Computer Science (miscellaneous) lcsh:TJ1-1570 Electrical and Electronic Engineering Mechanical Engineering Process (computing) multiple optimal solutions Electrochemical machining electrochemical machining (ECM) input parameter optimization split-optimization approach Range (mathematics) Control and Systems Engineering Filter (video) 020201 artificial intelligence & image processing |
| Zdroj: | Machines Volume 9 Issue 3 Machines, Vol 9, Iss 65, p 65 (2021) |
| ISSN: | 2075-1702 |
| DOI: | 10.3390/machines9030065 |
| Popis: | A tremendous amount of work has been done in the recent years in the optimization of input parameters, however, current optimization techniques can only provide a single optimal input process parameter combination. Although alternative techniques have been developed to provide multiple solutions with identical objective values, these techniques have low efficiency when searching for multiple solutions. In this paper, a two-stage filter split-optimization approach is proposed to obtain multiple solutions, at a higher efficiency than for a single-objective optimization problem. The aforementioned tasks are accomplished by first performing an initial split-optimization and then performing a second optimization after excluding input parameters from having their range split into sub-ranges based on the results of the initial optimization. The proposed approach enables the algorithm to explore input parameters that have a more significant impact on the objective function, thereby enabling it to find multiple optimal solutions more efficiently. The proposed approach was validated by using it to optimize the input process parameters of an electrochemical machining problem with five input parameters. The results from the case study show that though the proposed approach provided fewer optimal solutions it was able to obtain them at twice the efficiency when compared to the original method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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