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In recent years, synthesizing drugs powered by artificial intelligence has brought great convenience to society. Since retrosynthetic analysis occupies an essential position in synthetic chemistry, it has received broad attention from researchers. In this review, we comprehensively summarize the development process of retrosynthesis in the context of deep learning. This review covers all aspects of retrosynthesis, including datasets, models and tools. Specifically, we report representative models from academia, in addition to a detailed description of the available and stable platforms in the industry. We also discuss the disadvantages of the existing models and provide potential future trends, so that more abecedarians will quickly understand and participate in the family of retrosynthesis planning.

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Purpose Container shipping companies face various risks with different consequences that are required to be mitigated. Limited empirical research has been done on identifying and evaluating risk management strategies in shipping operations with different risk consequences. This paper aims to identify the appropriate risk mitigation strategies and evaluate the relative importance of these strategies. Design/methodology/approach Literature review and interviews were used to identify and validate the appropriate risk mitigation strategies in container shipping operations. A questionnaire with a Likert five-point scale was then conducted to rank the identified risk mitigation strategies in terms of their overall effectiveness. Top six important strategies were selected to evaluate their relative importance under three risk consequences (i.e. financial, reputation and safety and security incident related loss) through using another questionnaire with paired-comparison. Fuzzy analytic hierarchy process (AHP) was then conducted to analyse the paired-comparison questionnaire. Findings After conducting a systematic literature review and interviews, 18 mitigation strategies were identified. The results from the first questionnaire show that among the 18 strategies, the top three are “form alliances with other shipping companies”, “use more advanced infrastructures (hardware and software)” and “choose partners very carefully”. After conducting fuzzy AHP, the results show that shipping companies emphasize more on reducing the risk consequence of financial loss; and “form alliance with other shipping companies” is the most important risk mitigation strategy. Originality/value This paper evaluates the risk mitigation strategies against three risk consequences. Managers can benefit from the systematic identification of mitigation strategies, which shipping companies can consider for adoption to reduce the operational risk impact.

This paper considers a manufacturing supply chain with multiple suppliers in the presence of multiple uncertainties such as uncertain material supplies, stochastic production times, and random customer demands. The system is subject to supply and production capacity constraints. We formulate the integrated inventory management policy for raw material procurement and production control using the stochastic dynamic programming approach. We then investigate the supplier base reduction strategies and the supplier differentiation issue under the integrated inventory management policy. The qualitative relationships between the supplier base size, the supplier capabilities and the total expected cost are established. Insights into differentiating the procurement decisions to different suppliers are provided. The model further enables us to quantitatively achieve the trade-off between the supplier base reduction and the supplier capability improvement, and quantify the supplier differentiation in terms of procurement decisions. Numerical examples are given to illustrate the results

The outbreak of COVID-19 has significantly affected the development of enterprises. In the post-pandemic era, blockchain technology has become one of the important technologies to help enterprises quickly gain market competitiveness. The heavy investment required of supply chain stakeholders to employ blockchain technology has hindered its adoption and application. To tackle this issue, this study aims to facilitate the adoption of blockchain technology in a supply chain consisting of a core enterprise and a small/medium-sized enterprise through an effective supply chain contract. We analyze the performance of a cost-sharing (CS) contract and a revenue-sharing (RS) contract and propose a new hybrid CS-RS contract for better performance. We conduct comparative analyses of the three contracts and find that the hybrid CS-RS contract can more effectively incentivize both parties to reach the highest level of blockchain technology adoption and achieve supply chain coordination.