A Two-Stage Differential Evolution Algorithm with Mutation Strategy Combination

For most of differential evolution (DE) algorithm variants, premature convergence is still challenging. The main reason is that the exploration and exploitation are highly coupled in the existing works. To address this problem, we present a novel DE variant that can symmetrically decouple exploration and exploitation during the optimization process in this paper. In the algorithm, the whole population is divided into two symmetrical subpopulations by ascending order of fitness during each iteration; moreover, we divide the algorithm into two symmetrical stages according to the number of evaluations (FEs). On one hand, we introduce a mutation strategy, DE/current/1, which rarely appears in the literature. It can keep sufficient population diversity and fully explore the solution space, but its convergence speed gradually slows as iteration continues. To give full play to its advantages and avoid its disadvantages, we propose a heterogeneous two-stage double-subpopulation (HTSDS) mechanism. Four mutation strategies (including DE/current/1 and its modified version) with distinct search behaviors are assigned to superior and inferior subpopulations in two stages, which helps simultaneously and independently managing exploration and exploitation in different components. On the other hand, an adaptive two-stage partition (ATSP) strategy is proposed, which can adjust the stage partition parameter according to the complexity of the problem. Hence, a two-stage differential evolution algorithm with mutation strategy combination (TS-MSCDE) is proposed. Numerical experiments were conducted using CEC2017, CEC2020 and four real-world optimization problems from CEC2011. The results show that when computing resources are sufficient, the algorithm is competitive, especially for complex multimodal problems.

Green Product Quality Supervision Strategy in Online Shopping With Consumer Evaluation and Complaint

Green consumption is an important foundation for achieving stable and long-term economic development goals. With the rapid development of e-commerce and people’s widespread attention to sustainability, more and more consumers purchase green products online. Therefore, we consider consumer feedback mechanisms including evaluation and complaint and construct an evolutionary game model of green product quality supervision with the participation of governmental supervision department, third-party e-commerce platform, online seller and consumer, which analyzes the four parties’ evolutionary stable strategies. To verify the theoretical results, we conduct a numerical simulation by Matlab 2020b. Moreover, we study the conditions that make evolutionary stable strategy combination exist based on Lyapunov’s First Method. And we find that when consumer chooses complaint, (0, 0, 1) is likely to become an only evolutionary stable strategy combination. At this time, the online seller chooses to provide high-quality green product, third-party e-commerce platform chooses not to strengthen inspection, and governmental supervision department chooses to strictly supervise. Conversely, when the consumer chooses no complaint, (1, 0, 0) and (0, 0, 1) may become an evolutionary stable strategy combination. At this time, the online seller cannot be stable in providing high-quality green product. What’s more, governmental supervision department increases the penalty, which can incentivize a third-party e-commerce platform to strengthen inspection. Third-party e-commerce platform increases the reward and can promote online seller to provide high-quality green product. On the one hand, this paper enriches the theoretical basis of online shopping green product quality supervision. On the other hand, compared with existing literature, it extends the main body of the evolutionary game to four paries and broadens the application scope of the game model. In addition, it has put forward feasible suggestions for the government supervision department to strengthen the quality supervision, and provided decision-making support for the third-party e-commerce platform to assume the responsibility of quality inspection.

Estratégia, combinação e reticências

Este trabalho tem como objetivo discutir teoricamente aspectos da Estratégia como processo e como prática social. Assim, consiste em um ensaio teórico que caracteriza ambas as ênfases de pesquisa e aponta possibilidades de combinação entre essas tradições. Nesse contexto, fornece uma visão crítica, que aproxima a abordagem micro da Estratégia como prática a uma análise sociológica, enquanto a Estratégia como processo é tida como associada às práticas de gestão na Administração e ao seu ideário centrado no desempenho organizacional. Dessa forma, o trabalho, apesar de revisar recentes propostas internacionais de diálogo entre essas tradições, acaba por destacar a possível incomensurabilidade de combinação direta dessas abordagens, devido aos diferentes valores e crenças subjacentes aos enfoques no mercado ou na sociedade como o contexto primário das organizações. Palavras-chave: Administração. Estratégia como processo. Estratégia como prática. Strategy, combination and suspension points Absrtract This paper aims to theoretically discuss aspects of Strategy as a process and as a social practice. Thus, it consists of a theoretical essay that characterizes both research emphases and points out possibilities of combination between these traditions. In this context, it provides a critical view that approximate the micro approach of Strategy as practice to a sociological analysis, while Strategy as a process is considered to be associated with management practices in administration and its ideas centered on organizational performance. Thus, the work, despite reviewing recent international proposals for dialogue between these traditions, eventually highlights the possible incommensurability of direct combination of these approaches, due to the different values and beliefs underlying market or societal approaches as the primary context of organizations. Keywords: Management. Strategy as a process. Strategy as a practice.

Improvement of Envelope Design Through Multilayer Feed-Forward Neural Networks

The performance of the building envelope of a large-scale public building significantly influences the energy consumption of such a building. This study aims to determine the best strategy for the envelope by examining the engineering design of the building in Nanchang University. The building shape coefficient, sun-shading strategies, window–wall ratio, roof, and walls were studied through a method involving multilayer feed-forward neural network model simulations. Results show that the optimum shape coefficient value is 0.32. The combination of interior and exterior blinds and electrochromic glass is the ideal option to reduce the increase in the energy consumption of the architecture caused by solar radiation. Maintaining the window–wall ratio at 0.4 is ideal. A green roof exerts a minimal effect on building energy consumption decrease (only 0.4%). Applying the strategy of vertical greening to the external wall can reduce cooling energy consumption by as much as 5.4%. Adopting the best envelope strategy combination can further decrease energy consumption by 20.8%. This strategy is also applicable to the middle and lower reaches of Yangtze River in China, which flow through Nanchang and have a climate similar to that of the said area. Future research should be directed toward applying artificial neural networks to quantitatively evaluate the effects of a design strategy and produce the best design strategy combination.

Toward the development of versatile functionalized carbon nanotubes

A versatile and effective strategy combination of mussel inspired chemistry and SET-LRP has been developed for preparation of hydrophilic and hydrophobic carbon nanotubes for the first time.