The bare-bones differential evolutionary for stochastic joint replenishment with random number of imperfect items

Research on B2C Online Marketing Mode based on Multimodel Fusion and Intelligent Big Data Analysis Method

B2C online marketing mode is the development trend of future marketing. The key to improve the efficiency of such a mode is to make efficient use of the current large-scale data and mining the corresponding potential value. To control the cost of B2C online marketing mode, this paper analyzes the UJRP model and proposes a hybrid bat difference algorithm (BADE). Experimental results are verified the effectiveness of the proposed method in diversity and cost control. Furthermore, we utilize multimodel fusion strategy (linear weighted fusion) to achieve better performances in B2C online marketing on cost than BADE method. Finally, in the random and diverse online marketing environment, such an improved method can provide the decision-makers of B2C online marketing mode with more flexible choices.

Ensuring sustainability in the reverse supply chain in case of the ripple effect: A two-stage stochastic optimization model

The devastating impact of the ripple effect increases the importance of the reverse supply chain (RSC) design to ensure sustainability in the long-term. That being the case, in this study, a two-stage stochastic mixed-integer optimization model is proposed to design an RSC network under uncertainty sourcing from the ripple effect (i.e. external side of RSC) by considering the environmental and economic dimensions of sustainability. The environmental and economic disruptions of the ripple effect are represented by the increase in the carbon emission levels and the distance of roads, and the decrease in the capacity of facilities, respectively. Accordingly, a set of scenarios is considered based on the disruption levels (low- and high-impact) in case of the ripple effect. Furthermore, an α -reliability constraint is integrated into the model to further analyze the occurrence of scenarios. The model allows us to make integrated operational and strategic decisions by placing an emphasis on the carbon emission levels (i.e. environmental dimension) and the total cost (i.e. economic dimension). To obtain some remarkable insights, the proposed model is validated through computational experiments based on data extracted from a real case. The computational results show that the ripple effect increases the emission level and total cost up to 40%. For this reason, it suggested that the regulations regarding WEEE (Waste Electrical and Electronic Equipment) should be prepared by considering sustainability in the entire RSC network. Besides, it is realized that the centralized distribution strategy leads to a more resilient RSC network design.

Spatial analysis, coupling coordination, and efficiency evaluation of green innovation: A case study of the Yangtze River Economic Belt

Green innovation is an important driving force to promote the sustainable development of urban society and economy. This paper constructs an evaluation index system containing social undesirable outputs, and uses the Super-SBM model and the Malmquist-Luenberger index to evaluate green innovation efficiency in 42 cities along the Yangtze River Economic Belt from 2013 to 2017. Additionally, spatial autocorrelation analysis is used to study the spatial correlation of green innovation efficiency. Finally, the coupling coordination degree model is used to study the coupling coordination degree between green innovation efficiency and high-tech industries. The following results were obtained. (1) The average value of green innovation efficiency increased from 1.0446 to 1.0987, and the annual average growth rate of total factor productivity of green innovation was 1.1%. (2) Green innovation efficiency of the Yangtze River Economic Belt had a significant spatial positive correlation, but the types of agglomeration among cities in different sections of the Yangtze River were quite different. (3) The coupling coordination degree between green innovation efficiency and the development level of high-tech industries in the cities of the Yangtze River Economic Belt was in the basic coordination stage. Based on the research results, we suggest that cities in this belt further enhance the interactive relationship between green innovation and economic development and promote the coordinated development of economy and society.

An improved sequential auction with complementarity for pricing the construction land quota

The paradox between idle homesteads in rural areas and the shortage of construction land in urban areas is concerning. Hence, local governments encourage farmers to reclaim their idle homesteads and farmlands to generate quota. However, the current quota price, which is based on the land reclamation cost, is often inadequate to motivate farmers. This study proposed that the construction land quota and construction land are complementary items, and hence, their pricing should be studied simultaneously instead of independently. Therefore, the classical sequential auction model with complementarity was improved using the core characteristics of quota transactions and those were applied to design optimal pricing mechanisms. Subsequently, the influence of relevant factors on the bidding price was analysed. The results indicated that the bidding price decreases with an increase in the number of bidders and that a bidder’s revenue is at a loss when they acquire the quota but fail to obtain the land; hence, the revenue probability is lost. However, bidding prices increase when the fine of delaying construction increases. To raise the quota price and encourage relatively more farmers to reclaim their idle homesteads, local governments should appropriately increase the delaying construction fines or repurchase the quota at a premium from the bidder who acquires the quota but fails to obtain the land, which is beneficial for easing conflict between construction land demands and farmland protection and for promoting the sustainable development of China’s social economy.