Affiliation:
1. Department of Engineering , Durham University, Lower Mount Joy, South Road, Durham, DH1 3LE, UK
Abstract
Abstract
This paper takes the ant colony optimization (ACO) clustering algorithm as the starting point, explores the innovative ways of enterprise strategic management based on the background of economic goals of carbon peak and neutralization, and dynamically adjusts the transition probability according to the average number of node branches to make it ‘explore’ and ‘utilize’. A balance can always be maintained between the two so that the algorithm can provide more technical support in realizing the innovation and practice of operation, profit, and management of enterprises while retaining a high searchability, avoiding stagnation, and ultimately promoting the sustainable development of the enterprise. The experimental results show that compared with the three conventional methods, the proposed algorithm has a robust global analysis ability, so it has a better application effect in operation, profit, and management of enterprise innovation and efficiency improvement. The application of ACO clustering can be seen.
Publisher
Oxford University Press (OUP)
Reference30 articles.
1. Research on the relationship between China’s supply-side structural reform and enterprise innovation-from the perspective of financing constraints;Yin;World Sci Res J,2020
2. Role of operations management from the perspective of enterprise risk management in Indian industries for emerging market;Muthukrishnan;Strad,2021
3. Review of available SW solutions for intellectual property management systems from the perspective of open innovation;Krejcar;J Open Innov: Technol Mark Complex,2020
4. The incentives and efforts for innovation and entrepreneurship in a resource-based economy: a survey on perspective of Qatari residents;Tok;Sustainability,2020
5. Board and innovation: a systematic review of the literature from a contingency perspective;Belkacemi;Acad Manag Proc 2021,2021