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Facility planning and schedule design in the pandemic: Eliminating contacts at construction workplace.
Wang, Haoqing; Yi, Wen; Wang, Shuaian.
  • Wang H; Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China.
  • Yi W; Department of Building and Real Estate, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China.
  • Wang S; Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China.
J Clean Prod ; 395: 136394, 2023 Apr 01.
Article in English | MEDLINE | ID: covidwho-2236796
ABSTRACT
The construction industry has been severely affected by the COVID-19 pandemic and the associated restrictions on person-to-person contacts issued by the government. A construction site usually has a high number of workers working at the same time; therefore, the question of how to ensure their safety during the pandemic-that is, how to protect them from getting infected-has become an urgent problem. In this study, we propose a bi-objective integer programming model to establish the optimal schedule plan under COVID-19 regulations. We develop a solution method and conduct numerical experiments to solve and validate our model. The optimal schedule plan can avoid contacts between workers of different groups while minimizing the total costs of complying with government policy. Our proposed model can be applied in practice to help project managers establish a reasonable and cost-effective schedule plan. This study contributes to reducing the operating costs of contractors and protecting the health of construction workers.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Language: English Journal: J Clean Prod Year: 2023 Document Type: Article Affiliation country: J.jclepro.2023.136394

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Language: English Journal: J Clean Prod Year: 2023 Document Type: Article Affiliation country: J.jclepro.2023.136394