Locating Sugar Cane Loading Stations Under Variations in Cane Supply

Pathumnakul, Supachai; Sanmuang, Chatklao; Eua-Anant, Nawapak; Piewthongngam, Kullapapruk

doi:10.1142/s0217595912500285

Cited by 6 publications

(4 citation statements)

References 21 publications

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“…Furthermore, few scholars have performed clustering based on distance using modified fuzzy c means, centre of gravity and K-means algorithms (e.g. Pathumnakul et al 2012;Bosona and Gebresenbet 2011;Zamar et al 2017;Sutanto et al 2018). The density-based approach for clustering is overlooked in the studies mentioned above.…”

Section: Modelling Approaches For Fscsmentioning

confidence: 99%

Modelling supply chain network for procurement of food grains in India

Mogale

Ghadge

Kumar

et al. 2019

International Journal of Production Research

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The procurement of food grains from farmers and their transportation to regional level has become decisive due to increasing food demand and post-harvest losses in developing countries. To overcome these challenges, this paper attempts to develop a robust data-driven supply chain model for the efficient procurement of food grains in India. Following the data collected from three leading wheat producing Indian regions, a mixed-integer linear programming model is formulated for minimising total supply chain network costs and determining number and location of procurement centres. The NK Hybrid Genetic Algorithm (NKHGA) is employed to cluster the villages, along with a novel density-based approach to optimise the supply chain network. Sensitivity analysis indicates that policymakers should focus on creating an adequate number of procurement centres in each surplus state, well before the start of the harvesting season. The study is expected to benefit food grain supply chain stakeholders such as farmers, procurement agencies, logistics providers and government bodies in making an informed decision.

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Section: Modelling Approaches For Fscsmentioning

confidence: 99%

Modelling supply chain network for procurement of food grains in India

Mogale

Ghadge

Kumar

et al. 2019

International Journal of Production Research

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show abstract

“…Clustering is a process of partitioning data into clusters. Several clustering algorithms, such as k-means clustering, which is an algorithm for partitioning data into k distinct clusters, fuzzy c means, and center of gravity, used by researchers to decide the location of procurement centers in the context of food grain supply chain networks (Bosona & Gebresenbet, 2011;Pathumnakul et al, 2012;Sutanto et al, 2018;Zamar et al, 2017). Govindan et al (2014) and Saranwong and Likasiri (2017) considered the simultaneous use of location and transportation decisions in their studies of the food grain supply chain network.…”

Section: Modelling Of Supply Chain Network For the Procurement Of Food Grainsmentioning

confidence: 99%

Reconfiguration of food grain supply network amidst COVID-19 outbreak: an emerging economy perspective

et al. 2021

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The procurement of food grains from farmers is one of the biggest challenges under the COVID-19 outbreak due to country-wise lockdowns. The present study aims to reconfigure the existing food grain supply chain network. The study advances the extant literature by proposing a novel mathematical model that considers the government guidelines issued to procure food grains from farmers under the COVID-19 situation. The model includes personal distancing, a key parameter relevant in the COVID-19 crisis, and has remained unaddressed in the existing literature. The proposed model is tested in India. The effect of different parameters like personal distancing cost, carbon emission cost, fixed cost, and transportation cost is also investigated under a given set of procurement centers. Finally, the procurement schedule for each procurement center is generated, which is especially useful for managing its activities and is also helpful to farmers to streamline the process. Results indicate that the proposed model is highly effective under pandemic emergencies like the current COVID-19 crisis. Policymakers and the government will find this model helpful in drafting relevant policies regarding food grain procurement under emergencies such as the COVID-19 outbreak. The distribution segment of the supply chain network is not part of the present research work. In future studies, this part could be then added to the whole of the procurement process, and both procurement and distribution can be assessed together again.

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“…They study six real world examples. Pathumnakul et al [10] considered the different maturity times of sugarcane to find the optimal locations of the loading stations. They modify the fuzzy c-means method to consider cane maturity time as well as cane supply.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Stage 1 involves GIS analysis. As stated by Pathumnakul [10] clustering of farms is carried out in this stage. The goal of this stage is to generate an origin-destination (O-D) matrix.…”

Section: Stage 1: Gis Analysis With Clusteringmentioning

confidence: 99%

Location Allocation of Sugar Beet Piling Centers Using GIS and Optimization

Dharmadhikari¹,

Farahmand

2019

Infrastructures

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The sugar beet is one of the most important crops for both social and economic reasons, even though the area under sugar beet cultivation in the Red River valley of North Dakota and Minnesota is comparatively smaller that of corn and other crop lands. It generates a large economic activity in local and regional level with a greater impact on jobs and stimulation of agriculture, transportation, and farm economy. Sugar beet transportation takes place in two stages in Red River Valley: the first step is from farms to piling centers (pilers) and the second step from pilers to processing facilities. This study focuses on the problem of optimizing piler locations based on supply variation. Sugar beet supply and harvest varies significantly due to numerous reasons such as weather, water availability, and different maturity dates for the crop. This provides for a variable optimal harvesting time based on the plant maturity and sugar content. Sub-optimized pilers location result in the high transportation and utilization costs. The objective of this study is to minimize the sum of transportation costs to and from pilers and the pilers utilization cost. A two-step algorithm based on the geographical information system (GIS) with global optimization method is used to solve this problem. This method will also be useful for infrastructure decision makers such as planners and engineers to predict the truck volume on rural roads.

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Locating Sugar Cane Loading Stations Under Variations in Cane Supply

Cited by 6 publications

References 21 publications

Modelling supply chain network for procurement of food grains in India

Modelling supply chain network for procurement of food grains in India

Reconfiguration of food grain supply network amidst COVID-19 outbreak: an emerging economy perspective

Location Allocation of Sugar Beet Piling Centers Using GIS and Optimization

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