A Multimodal, Multicommodity, and Multiperiod Planning Problem for Coal Distribution to Poor Families
| dc.contributor.author | Akgun, Ibrahim | |
| dc.contributor.author | Ozkil, Altan | |
| dc.contributor.author | Goren, Selcuk | |
| dc.date.accessioned | 2025-09-25T10:39:14Z | |
| dc.date.available | 2025-09-25T10:39:14Z | |
| dc.date.issued | 2020-12 | |
| dc.description | Akgun, Ibrahim/0000-0001-6325-7741; Goren, Selcuk/0000-0002-5320-4213 | en_US |
| dc.description.abstract | Tackling poverty has been one of the greatest global challenges and a prerequisite to sustainable development of countries. Countries implement nationally appropriate social protection systems and measures to address poverty. This paper addresses an aid system adopted by the government in Turkey where significant amounts of coal is distributed to poor families each year. The objective of the coal aid system is to complete the delivery of coal to poor families by the start of winter. However, an analysis of the data from previous years indicates that the distribution to many families cannot be completed on time. This results from the fact that planning is done manually and by trial-and-error as there is no system that can be used for distribution planning. This paper describes the planning problem encountered and develops a mathematical model to solve it. The proposed model is a multimodal, multicommodity, and multiperiod linear programming (LP) model. The model can be used to develop and update a distribution plan as well as to answer several what-if questions with regard to capacities, time constraints, and so forth. The model is solved using CPLEX for several problem instances obtained under different scenarios using data for the year 2012. The results show that at least 9% cost savings and about 40% decrease in distribution completion time can be achieved when the model is used. We analyze scenario results qualitatively and quantitatively and provide several insights to the decision makers. As a part of quantitative analysis, we develop regression models to predict optimal costs based on several factors. Our main contribution is to provide an efficient and effective tool to handle a large-scale real-world problem. The model has also helped to prove that the organization responsible for distribution planning may move from the current planning practice to an all-encompassing top-down approach. | en_US |
| dc.description.sponsorship | TCE | en_US |
| dc.description.sponsorship | This research has been supported by the TCE. The authors are grateful to anonymous referees for providing constructive feedback that has helped improve in major ways the presentation of the material in the paper. | en_US |
| dc.description.sponsorship | The distribution of coal from mines to poor families is conducted in two phases. In the first phase, coal is transported from mines to delivery locations in the districts that are determined by the SASFs. In this phase, road transport or a combination of rail and road transport may be used. In the former, coal is loaded onto trucks at the mines and moved to the delivery locations in the districts by trucks. In the latter, coal is loaded onto railcars at the mines and moved to a destination station by train. At the destination station, coal is unloaded from railcars and loaded onto trucks for further transportation to delivery locations in the districts. In the second phase, coal is moved from delivery locations to families within districts by trucks. The TCE is responsible for the first phase while the SASF in each district is responsible for the second phase. However, the TCE may also request the support of the foundations when needed in the first phase, e.g., for arranging regional or local distribution.This research has been supported by the TCE. The authors are grateful to anonymous referees for providing constructive feedback that has helped improve in major ways the presentation of the material in the paper. | |
| dc.description.sponsorship | SASF; Thiagarajar College of Engineering, TCE | |
| dc.identifier.doi | 10.1016/j.seps.2020.100919 | |
| dc.identifier.issn | 0038-0121 | |
| dc.identifier.issn | 1873-6041 | |
| dc.identifier.scopus | 2-s2.0-85089194309 | |
| dc.identifier.uri | https://doi.org/10.1016/j.seps.2020.100919 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12573/3105 | |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier Science inc | en_US |
| dc.relation.ispartof | Socio-Economic Planning Sciences | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Freight Transportation | en_US |
| dc.subject | Public Sector Operations Research | en_US |
| dc.subject | UN Sustainable Development Goals | en_US |
| dc.subject | Network Optimization | en_US |
| dc.subject | Multimodal | en_US |
| dc.subject | Multicommodity | en_US |
| dc.subject | Multiperiod Planning | en_US |
| dc.subject | Multimodal, | |
| dc.subject | Multicommodity, | |
| dc.title | A Multimodal, Multicommodity, and Multiperiod Planning Problem for Coal Distribution to Poor Families | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication | |
| gdc.author.id | Akgun, Ibrahim/0000-0001-6325-7741 | |
| gdc.author.id | Goren, Selcuk/0000-0002-5320-4213 | |
| gdc.author.scopusid | 14626136300 | |
| gdc.author.scopusid | 56139404700 | |
| gdc.author.scopusid | 14520483500 | |
| gdc.author.wosid | Akgun, Ibrahim/R-8752-2019 | |
| gdc.author.wosid | Gören, Selçuk/Abc-1985-2020 | |
| gdc.bip.impulseclass | C5 | |
| gdc.bip.influenceclass | C5 | |
| gdc.bip.popularityclass | C5 | |
| gdc.coar.access | metadata only access | |
| gdc.coar.type | text::journal::journal article | |
| gdc.collaboration.industrial | false | |
| gdc.description.department | Abdullah Gül University | en_US |
| gdc.description.departmenttemp | [Akgun, Ibrahim; Goren, Selcuk] Abdullah Gul Univ, Dept Ind Engn, Kayseri, Turkey; [Ozkil, Altan] Atilim Univ, Dept Aviat Management, Ankara, Turkey | en_US |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | Q1 | |
| gdc.description.startpage | 100919 | |
| gdc.description.volume | 72 | en_US |
| gdc.description.woscitationindex | Science Citation Index Expanded - Social Science Citation Index | |
| gdc.description.wosquality | Q1 | |
| gdc.identifier.openalex | W3046882466 | |
| gdc.identifier.wos | WOS:000595279900010 | |
| gdc.index.type | WoS | |
| gdc.index.type | Scopus | |
| gdc.oaire.diamondjournal | false | |
| gdc.oaire.impulse | 2.0 | |
| gdc.oaire.influence | 2.514786E-9 | |
| gdc.oaire.isgreen | false | |
| gdc.oaire.popularity | 3.1022505E-9 | |
| gdc.oaire.publicfunded | false | |
| gdc.oaire.sciencefields | 0502 economics and business | |
| gdc.oaire.sciencefields | 05 social sciences | |
| gdc.oaire.sciencefields | 0211 other engineering and technologies | |
| gdc.oaire.sciencefields | 02 engineering and technology | |
| gdc.openalex.collaboration | National | |
| gdc.openalex.fwci | 0.11 | |
| gdc.openalex.normalizedpercentile | 0.39 | |
| gdc.opencitations.count | 2 | |
| gdc.plumx.crossrefcites | 2 | |
| gdc.plumx.mendeley | 53 | |
| gdc.plumx.scopuscites | 4 | |
| gdc.scopus.citedcount | 4 | |
| gdc.wos.citedcount | 4 | |
| relation.isOrgUnitOfPublication.latestForDiscovery | 665d3039-05f8-4a25-9a3c-b9550bffecef |
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