0
Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Human Health Effects Policy & Risk Sign in to save

A Multi-Objective Optimization Model for Multi-Facility Decisions of Infectious Waste Transshipment and Disposal

Sustainability 2023 1 citation ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Prasit Kailomsom, Charoenchai Khompatraporn

Summary

Researchers developed a multi-objective optimization model for infectious waste disposal balancing economic, social, and environmental concerns using consolidation facilities.

Infectious waste disposal is a crucial concern in many areas. Not only is the waste obnoxious, but it can also pose a vital risk to human health. Disposal of infectious waste incurs higher costs than general waste disposal and must abide by stricter regulations. In this paper, the infectious waste disposal is formulated as a multi-objective optimization model. The objectives encompass economic, social, and environmental concerns. To save cost, waste transshipment facilities to function as consolidation points are proposed and integrated in the model. The economic objective includes construction and operational costs of the transshipment and disposal facilities. The social objective considers the communities surrounding the disposal facilities, while carbon dioxide emission is used as the measure in the environmental objective. The model is reformulated based on the lexicographic weighted Tchebycheff method to ensure that the Pareto frontier of the solutions is obtained. Then the model is applied to a health region in Thailand. Daily and every-other-day waste collection intervals are compared to examine additional benefits. Certain sensitivity of the solutions is also analyzed. After comparing several solutions, a compromise among all three objectives is suggested. It is composed of three transshipment and two disposal facilities, each with 1000 kg capacity. Moreover, if the solution is executed with the every-other-day waste collection interval, the overall costs can be saved. A sensitivity analysis of the solution on fuel price found that the solution was not very sensitive against an increase in the fuel price, in that when the fuel price increased by 20% the overall costs only increased by 7%. Lastly, when the daily infectious wastes are doubled, all the objective function values rise, ranging from 56% to 163%. The new solution suggests an increase in the number of the disposal facilities to four, but a decrease of the transshipment ones to only two.

Sign in to start a discussion.

More Papers Like This

Article Tier 2

Medical waste management during coronavirus disease 2019 pandemic at the city level

Researchers developed an integrated medical waste management model incorporating uncertain waste generation estimates and pickup routing optimization for COVID-19-related infectious waste at the city level, applying optimistic, realistic, and pessimistic scenarios to guide waste treatment center placement and route planning in Turkey.

Article Tier 2

Reduction of cost and emissions by using recycling and waste management system

An optimization model for integrated waste management systems was developed with dual objectives of minimizing cost and greenhouse gas emissions, demonstrating that simultaneous economic and environmental goals can be achieved through system-level design. The model provides a tool for sustainable waste management planning.

Article Tier 2

Optimizing plastics recycling networks

Researchers developed mathematical optimization models — including linear programming tools — to help plan efficient plastic recycling networks that can tolerate some contamination from mixed plastic waste streams. These models could help overcome a key barrier to large-scale recycling by intelligently matching waste sources with the plants best equipped to handle them.

Article Tier 2

A hybrid machine learning-mathematical programming optimization approach for municipal solid waste management during the pandemic

Researchers combined machine learning forecasting with mathematical supply-chain optimization to model municipal solid waste management in New York City under COVID-19 conditions, revealing trade-offs between economic efficiency and landfill diversion that could inform planning for future pandemic scenarios.

Article Tier 2

Rank and Analysis Several Solutions of Healthcare Waste to Achieve Cost Effectiveness and Sustainability Using Neutrosophic MCDM Model

Researchers developed a multi-criterion decision-making framework using neutrosophic logic to rank healthcare waste management solutions for cost-effectiveness and sustainability. The study applied an improved ELECTRE method under conditions of uncertainty to evaluate different treatment options, accounting for varying levels of decision-maker expertise. The findings provide a systematic approach for developing countries to improve healthcare waste disposal practices while balancing financial and environmental considerations.

Share this paper