Location and allocation optimization for integrated decisions on post-disaster waste supply chain management: On-site and off-site separation for recyclable materials

Boonmee, Chawis; Arimura, Mikiharu; Asada, Takumi

doi:10.1016/j.ijdrr.2018.07.003

Cited by 38 publications

(26 citation statements)

References 31 publications

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“…Decisions also need to be made about if the wastes are to be incinerated, landfilled, or recycled (Boonmee et al, 2018). Generally, the support models are designed to help to achieve the goal of cost minimization, and they are also limited to constraints based on the actual disaster contexts.…”

Section: Waste Management Systemsmentioning

confidence: 99%

“…),Francesco et al (2018),Regattieri et al (2018),Boonmee et al (2018),Otsuka and Katsumi (2015),,Ozdamar et al (2014),Lesperance et al (2011), Zawawi et al (2018,Yoo et al (2017),Zawawi et al (2015),Maryono et al (2015),Caniato et al (2016),Regattieri et al (2016) andBaek et al (2016); 23EarthquakeSasao (2016),Asari. et al (2013),,Xiao et al (2012), García-Torres et al (2018), Berktas et al (2016), Çelik et al (2015), Sahin et al (2016), Domingo and Luo (2017), Karunasena and Amaratunga (2016; 2015), Shibata et al (2012), Kawamoto and Kim (2016, 2019), Faleschini et al (2017), Onan et al (2015), Wakabayashi et al (2017), Askarizadeh et al (2016), Saffarzadeh et al (2017), Hu and Sheu (2013), Raila and Anderson (2017), Poudel et al (2018), Cheng et al (2018a), Karunasena et al (2012), Pham et al (2014), Askarizadeh et al (2017), Sakai et al (2019), Pramudita and Taniguchi (2014), Memon (2015), Zhang et al (2016), Hooper (2019) and Koyama et al (2016); 33 Tsunami Asari et al (2013), Prasetya et al (2012), Tabata et al (2017), Wakabayashi et al (2017), Pereira-Portugal and Lee (2016) and Koyama et al (2016); 6 Hurricane/Typhoon Fetter and Rakes (2011; 2012), Habib.…”

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confidence: 99%

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A systematic review of recent developments in disaster waste management

Zhang

Cao

et al. 2019

Journal of Cleaner Production

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Disaster waste management received increasing attention in recent year, but there was no review updating the evolving development after the study of Brown et al. (2011a). To explore how the topics in disaster waste management evolved in recent years and to analyze whether the gaps identified by Brown et al. (2011a) are covered, 82 papers published from 2011 to 2019 were selected from the Scopus database based on the defined process and criteria, to systematically examine the disaster waste management research from nine aspects of planning, waste, waste treatment options, environment, economics, social considerations, organizational aspects, legal frameworks and funding. The results suggested that there were no obvious changes or developments in the field of disaster waste management, although a few research gaps have been addressed, such as waste separation, waste quantities, case studies of incineration and waste to energy, direct economic effects, social considerations as well as application of GIS technology. Except for the comparative studies, future directions were suggested by the gaps that persist since Brown et al. (2011a) and the new gaps that were identified in this review.

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Section: Waste Management Systemsmentioning

confidence: 99%

mentioning

confidence: 99%

A systematic review of recent developments in disaster waste management

Zhang

Cao

et al. 2019

Journal of Cleaner Production

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“…Davoodi and Goli [49] minimize the arrival time of aid vehicles to disaster areas using hybrid bender decomposition and variable neighborhood search. Boonmee et al [50] present a post-disaster waste management model, including a recycling decision model. A mixed integer programming model is presented that is solved with Particle Swarm Optimization and Differential Evolution.…”

Section: Type Of Problemmentioning

confidence: 99%

Metaheuristics in the Humanitarian Supply Chain

et al. 2021

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Everyday there are more disasters that require Humanitarian Supply Chain (HSC) attention; generally these problems are difficult to solve in reasonable computational time and metaheuristics (MHs) are the indicated solution algorithms. To our knowledge, there has not been a review article on MHs applied to HSC. In this work, 78 articles were extracted from 2016 publications using systematic literature review methodology and were analyzed to answer two research questions: (1) How are the HSC problems that have been solved from Metaheuristics classified? (2) What is the gap found to accomplish future research in Metaheuristics in HSC? After classifying them into deterministic (52.56%) and non-deterministic (47.44%) problems; post-disaster (51.28%), pre-disaster (14.10%) and integrated (34.62%); facility location (41.03%), distribution (71.79%), inventory (11.54%) and mass evacuation (10.26%); single (46.15%) and multiple objective functions (53.85%), single (76.92%) and multiple (23.07%) period; and the type of Metaheuristic: Metaphor (71.79%) with genetic algorithms and particle swarm optimization as the most used; and non-metaphor based (28.20%), in which search algorithms are mostly used; it is concluded that, to consider the uncertainty of the real context, future research should be done in non-deterministic and multi-period problems that integrate pre- and post-disaster stages, that increasingly include problems such as inventory and mass evacuation and in which new multi-objective MHs are tested.

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“…To reduce the system's total cost, the model worked for the Polyethylene Terephthalate waste generation problem in Northern Mexico. Furthermore, a mixed-integer linear programme was used by Boonmee et al [28] to reduce the financial influence of a MSW while maximizing the revenue obtainable from selling waste. The work further employed the differential and particle swarm optimisation to analyse the proposed model.…”

Section: Applied Environmental Researchmentioning

confidence: 99%

A Workforce and Truck Allocation Model in a Solid Waste Management System: A Case from Nigeria

Ighravwe

Oke

2021

App. Envi. Res.

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The management of waste with the limited workforce and trucks is a complicated problem. Currently, there is insufficient evidence in literature on how this process could be optimised. In this article, two new models on genetic algorithm and differential evolution were developed to jointly optimise the cost and human reliability of a municipal solid waste (MSW). It optimised this system’s benefit-cost and established the relationship between a MSW’s workforce and truck allocation. Although prior research has revealed relationships among cost, workforce strength, and truck allocation activities, however, the nature of this relationship and the unique attribute of workers’ reliability to influence the total operating cost and the benefit-cost ratio have not been thoroughly understood. A case study of a MSW agency in Nigeria was used to demonstrate the applicability of the proposed model. The results obtained showed preference to the differential evolution algorithm’s results. This article contributes to MSW in the following ways: it presents a model to assign reliability to workforce in a MSW system based on evolutionary algorithms performance, and it optimises a MSW system’s total operating cost and the benefit-cost ratio concurrently.

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Location and allocation optimization for integrated decisions on post-disaster waste supply chain management: On-site and off-site separation for recyclable materials

Cited by 38 publications

References 31 publications

A systematic review of recent developments in disaster waste management

A systematic review of recent developments in disaster waste management

Metaheuristics in the Humanitarian Supply Chain

A Workforce and Truck Allocation Model in a Solid Waste Management System: A Case from Nigeria

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