| Autor: |
Weidong Chen, Junnan Wang, Guanyi Yu, Yumeng Hu |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Applied Sciences, Vol 12, Iss 13, p 6456 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2076-3417 |
| DOI: |
10.3390/app12136456 |
| Popis: |
With the increasing influence of climate change, green development has become an important trend. Since manufacturing represents approximately one-half of total energy consumption, reducing the amount of energy consumed within this industry is imperative. This study provides a hybrid flow shop scheduling issue under a time-of-use and ladder electricity price system to reduce total energy consumption without compromising maximum completion time. An improved non-dominated sorting genetic algorithm II with some optimization strategies is proposed to solve the problem. First, an enhanced constructive heuristic algorithm is used to improve the quantity of initial solution in the initialization. Besides, an adaptive genetic operation is introduced, aiming to avoid the emergence of locally optimal solutions. In addition, the right-shift approach is developed to reduce the total energy consumption without affecting completion time. By maintaining the production efficiency and reducing the energy consumption cost by 4.33%. A trade-off proposal is made between productivity and sustainability in view of the calculation results. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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