Numerical investigation on welding process parameters optimisation using multi-objective optimisation technique

Pinto, Mark Christhian Barrueta; Li, Yongbo

doi:10.1504/ijaom.2020.109788

Cited by 1 publication

(1 citation statement)

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“…Previous researchers have eagerly attempted to find the appropriate methods to solve multi-objective problems ( Mardan et al, 2019 , Pinto and Li, 2020 , Sosa and Dhodiya, 2021 ). The goal programming method is one of the most popular methods in this regard ( Zandkarimkhani et al, 2020 ).…”

Section: Proposed Modelmentioning

confidence: 99%

Medical waste management during coronavirus disease 2019 (COVID-19) outbreak: A mathematical programming model

Govindan

Nasr

Mostafazadeh

et al. 2021

Computers & Industrial Engineering

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Municipal solid waste (MSW) directly impacts community health and environmental degradation; therefore, the management of MSW is crucial. Medical waste is a specific type of MSW which is generally divided into two categories: infectious and non-infectious. Wastes generated by coronavirus disease 2019 (COVID-19) are classified among infectious medical wastes; moreover, these wastes are hazardous because they threaten the environment and living organisms if they are not appropriately managed. This paper develops a bi-objective mixed-integer linear programming model for medical waste management during the COVID-19 outbreak. The proposed model minimizes the total costs and risks, simultaneously, of the population’s exposure to pollution. This paper considers some realistic assumptions for the first time, including location-routing problem, time window-based green vehicle routing problem, vehicles scheduling, vehicles failure, split delivery, population risk, and load-dependent fuel consumption to manage both infectious and non-infectious medical waste. We apply a fuzzy goal programming approach for solving the proposed bi-objective model, and the efficiency of the proposed model and solution approach is assessed using data related to 13 nodes of medical waste production in a location west of Tehran.

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