- Tytuł:
- Quantum inspired chaotic salpswarm optimization for dynamicoptimization
- Autorzy:
-
Pathak, Sanjai
Mani, Ashish
Sharma, Mayank
Chatterjee, Amlan - Tematy:
-
computational intelligence
swarm intelligence
salp swarm algorithm
dynamic optimization
quantum computing - Pokaż więcej
- Wydawca:
- Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
- Powiązania:
- https://bibliotekanauki.pl/articles/58810102.pdf Link otwiera się w nowym oknie
- Opis:
- Many real-world problems are dynamic optimization problems that are un-known beforehand. In practice, unpredictable events such as the arrival of newjobs, due date changes, and reservation cancellations, changes in parametersor constraints make the search environment dynamic. Many algorithms aredesigned to deal with stationary optimization problems, but these algorithmsdo not face dynamic optimization problems or manage them correctly. Al-though some optimization algorithms are proposed to deal with the changesin dynamic environments differently, there are still areas of improvement inexisting algorithms due to limitations or drawbacks, especially in terms of lo-cating and following the previously identified optima. With this in mind, westudied a variant of SSA known as QSSO, which integrates the principles ofquantum computing. An attempt is made to improve the overall performanceof standard SSA to deal with the dynamic environment effectively by locatingand tracking the global optima for DOPs. This work is an extension of theproposed new algorithm QSSO, known as the Quantum-inspired Chaotic SalpSwarm Optimization (QCSSO) Algorithm, which details the various approachesconsidered while solving DOPs. A chaotic operator is employed with quantumcomputing to respond to change and guarantee to increase individual searcha-bility by improving population diversity and the speed at which the algorithmconverges. We experimented by evaluating QCSSO on a well-known general-ized dynamic benchmark problem (GDBG) provided for CEC 2009, followedby a comparative numerical study with well-regarded algorithms. As promised,the introduced QCSSO is discovered as the rival algorithm for DOPs.
- Dostawca treści:
- Biblioteka Nauki
Artykuł