Elsevier

Waste Management

Volume 69, November 2017, Pages 518-534
Waste Management

An optimization model for collection, haul, transfer, treatment and disposal of infectious medical waste: Application to a Greek region

https://doi.org/10.1016/j.wasman.2017.08.037Get rights and content

Highlights

  • We developed an optimization model to minimize cost of infectious waste management.

  • Two different software were used for model solution.

  • Model optimizes locations and capacities of treatment plants and transfer stations.

  • The higher percentage of total cost was due to construction of the treatment plant.

  • Sensitivity analysis with respect to fuel cost and waste production was conducted.

Abstract

The objective of this work was to develop an optimization model to minimize the cost of a collection, haul, transfer, treatment and disposal system for infectious medical waste (IMW). The model calculates the optimum locations of the treatment facilities and transfer stations, their design capacities (t/d), the number and capacities of all waste collection, transport and transfer vehicles and their optimum transport path and the minimum IMW management system cost. Waste production nodes (hospitals, healthcare centers, peripheral health offices, private clinics and physicians in private practice) and their IMW production rates were specified and used as model inputs. The candidate locations of the treatment facilities, transfer stations and sanitary landfills were designated, using a GIS-based methodology. Specifically, Mapinfo software with exclusion criteria for non-appropriate areas was used for siting candidate locations for the construction of the treatment plant and calculating the distance and travel time of all possible vehicle routes. The objective function was a non-linear equation, which minimized the total collection, transport, treatment and disposal cost. Total cost comprised capital and operation costs for: (1) treatment plant, (2) waste transfer stations, (3) waste transport and transfer vehicles and (4) waste collection bins and hospital boxes. Binary variables were used to decide whether a treatment plant and/or a transfer station should be constructed and whether a collection route between two or more nodes should be followed. Microsoft excel software was used as installation platform of the optimization model. For the execution of the optimization routine, two completely different software were used and the results were compared, thus, resulting in higher reliability and validity of the results. The first software was Evolver, which is based on the use of genetic algorithms. The second one was Crystal Ball, which is based on Monte Carlo simulation. The model was applied to the Region of East Macedonia – Thrace in Greece. The optimum solution resulted in one treatment plant located in the sanitary landfill area of Chrysoupolis, required no transfer stations and had a total management cost of 38,800 €/month or 809 €/t. If a treatment plant is sited in the most eastern part of the Region, i.e., the industrial area of Alexandroupolis, the optimum solution would result in a transfer station of 23 m3, located near Kavala General Hospital, and a total cost of 39,800 €/month or 831 €/t. A sensitivity analysis was conducted and two alternative scenarios were optimized. In the first scenario, a 15% rise in fuel cost and in the second scenario a 25% rise in IMW production were considered. At the end, a cost calculation in €/t/km for every type of vehicle used for haul and transfer was conducted. Also, the cost of the whole system was itemized and calculated in €/t/km and €/t. The results showed that the higher percentage of the total cost was due to the construction of the treatment plant.

Introduction

Mathematical programming has been used to optimize municipal solid waste (MSW) management systems, including haul and transfer (Abdelli et al., 2016, Laureri et al., 2016, Son and Louati, 2016, Das and Bhattacharyya, 2015, Sanjeevi and Shahabudeen, 2016, Hemmelmayr et al., 2013a, Hemmelmayr et al., 2013b, Zsigraiova et al., 2013, Chatzouridis and Komilis, 2012, Apaydin and Gonullu, 2011, Faccio et al., 2011, Kuo and Wang, 2011, Gupta and Sharma, 2011, Arribas et al., 2010). Such techniques have also been used for healthcare waste, but the applications are very limited (Budak and Ustundag, 2013, Almeida, 2011, Shih and Lin, 2003, Shi et al., 2009). For example, Shih and Lin (2003) used dynamic programming and integer linear programming methods with multicriteria optimization for planning of infectious medical waste (IMW) collection systems. Shi et al. (2009) presented a mixed integer linear programming model with cost minimization for medical waste reverse logistics networks and used a genetic algorithm method to solve the proposed model. Budak and Ustundag (2013) developed a mixed integer linear programming model to determine the optimal number and location of the facilities, by minimizing total cost. Other authors used GIS tools to optimize health care waste management systems (Shanmugasundaram et al., 2012, Alagoz and Kocasoy, 2008). Chaerul et al. (2008) used a goal programming approach for resolving complexities in healthcare waste management.

Voudrias and Graikos (2014) presented a preliminary design of an IMW management system for the Region of East Macedonia-Thrace (ΕΜΤR) in Greece. Steam sterilization was used as the treatment technology, but the siting of the treatment plant was not optimized and was placed in the geographic center of the region. Although a collection and transport plan was proposed, the authors indicated that there are several potential such plans, which could be evaluated for selection of the optimum one. Siting of formal transfer stations (TSs) was not considered, instead IMW storage rooms in public hospitals would be used as collection points in each prefecture. However, siting of TSs for IMW hauling is a significant issue regarding management cost minimization, but only sparingly has been addressed (Budak and Ustundag, 2013, Almeida, 2011). Although it is customary to collect and treat IMW from a few large producers, it is difficult and expensive to collect IMW from many widely spread small producers and this is the situation in which use of TSs may be necessary.

TSs for medical waste are operated in the United States, for example in the states of California, Florida, Texas, New York, etc. The medical waste management program of the Public Health Department of the State of California presents tables with medical waste TSs and treatment facilities (CDPH, 2017). The operation of such TSs for medical waste only recently (2012) was introduced in Greece (CMD, 2012). It is apparent that optimization of the system components is necessary to achieve management cost minimization.

The objective of this work was to develop an optimization model to design a collection, haul, transfer, treatment and disposal system for IMW. The model output includes the exact locations of the treatment facilities and TSs, their design capacities (t/d), the number and capacities of all waste collection, transport and transfer vehicles and their optimum transport path, as well as the minimum total management cost. The model was applied to the EMTR in Greece, for which IMW data were available (Voudrias and Graikos, 2014, Graikos et al., 2010, Kizlary et al., 2005, Mandalidis, 2011).

The paper has the following elements of novelty. It extended previous work by Chatzouridis and Komilis (2012) on MSW, by including treatment facilities in the model. In addition, there are significant differences between MSW and medical waste. For example, quantities of IMW are significantly smaller than those of MSW for the same population, with production nodes widely spread. Because IMW is a hazardous waste, special precautions and measures are necessary. For example, there are limits on storage temperature and time and the characteristics of the waste collection vehicles (Voudrias and Graikos, 2014). The novelty in the methodology is that IMW collection is not conducted on the same day for all producers, but varies, depending on the amounts produced. For example, collection frequency for a peripheral health office could be once a month, for a healthcare center once a week, whereas for a hospital every day. This differs from the approach applied in many MSW collection and transport models, but it is necessary to reduce collection and haul cost. However, this introduces significant complexity to the mathematical model, which was developed in this paper. Thus, our objective function is much different from the published for MSW models with constant daily collection patterns. Finally, operation of TSs in IMW management systems along with economic data for TSs and special collection vehicles and bins originating from primary sources are provided. The model can be applied to IMW management problems, in which only candidate locations for the treatment plants and TSs are previously defined and the model determines their numbers, exact locations and capacities.

Section snippets

Methodology

The proposed methodology consisted of the following four parts: (1) Exclusion of inappropriate areas for the construction of treatment facilities, (2) siting of all candidate IMW TSs and possible positions of treatment facilities for IMW, (3) model development in a user-friendly environment, such as an Excel® spreadsheet, to minimize total system cost and (4) model application.

IMW sources

EMTR occupies a total area of 14,157 km2, which is the 10.7% of the area of Greece. Its population is 606,170 residents (based on the 2011 census), which is approximately the 5.6% of the population of Greece. EMTR is divided in 5 prefectures (Drama, Kavala, Xanthi, Rodopi and Evros). Two islands, Thasos and Samothraki, belong to the Prefectures of Kavala and Evros, respectively. There are two public hospitals located in the Prefecture of Evros and one major public hospital in the capital city

Optimization results

Taking into account all candidate areas of Fig. 4, the application of the optimization model showed directly that the optimal location of the treatment facility in EMTR was in the wider sanitary landfill area of Chrysoupolis. According to Table 4, the optimal solution (38,800 €/month or 809 €/t) with the treatment facility located in the wider sanitary landfill area of Chrysoupolis (35 km from the industrial area of Xanthi) required no TSs. All WCVs depart from the treatment facility and one WCV

Conclusions

In this work, a conceptual model was developed to optimize the design of a collection, haul, transfer, treatment and disposal system for infectious medical waste. The system consists of IMW production nodes (groups of IMW producers), the intermediate nodes of TSs, the obligatory intermediate nodes of treatment facilities and finally the terminal nodes (landfills). The model calculates the optimum locations of the treatment facilities and TSs, their design capacities (t/d), the number and

Acknowledgement

The authors wish to thank Mr. I. Papaspyros for his assistance in using the Crystal Ball and Evolver software.

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