新冠病毒肺炎疫情对整个经济社会发展造成了很大冲击，如何在不放松疫情防控的前提下科学规划企业复工复产，这是地方政府面临的一个重要挑战。基于浙江省在统筹疫情防控和经济社会发展工作中的有关经验，本文建立了一个疫情条件下企业复工复产规划问题的整数规划模型，其目的是要在不违反疫情传播风险等约束下，从大批申请企业中选择一部分批准复工复产并安排优先顺序，以尽可能满足社会对相关产业产能的需求。为有效求解该问题，本文提出了一个改进的禁忌搜索算法，它使用贪心策略来构造一个初始解，并不断通过可变规模的邻域搜索来探寻更优的解，在多个地区企业复工复产规划问题实例上的计算结果验证了该算法的效率。
The outbreak of the novel coronavirus pneumonia (COVID-19) has caused a great impact on the whole economic and social development. It is an important challenge for local governments to plan the production resumption of enterprises without relaxing the epidemic prevention and control. Based on the experiences of Zhejiang Province in overall planning of epidemic prevention and control and economic development, in this paper, we formulate a production resumption planning problem, which selects a subset of enterprises from a large number of candidates that apply for production resumption and determines their order of resumption under epidemics, so as to satisfy the social demand for industrial capacities as much as possible without violating the constraints such as epidemic spreading risk. To efficiently solve this problem, we propose an improved tabu search algorithm, which uses a greedy strategy to construct an initial solution and continually explores a better solution based on variable neighborhood search. Computational results on enterprise production resumption planning in several regions demonstrates the efficiency of our method.
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