Search Results Heading

MBRLSearchResults

mbrl.module.common.modules.added.book.to.shelf
Title added to your shelf!
View what I already have on My Shelf.
Oops! Something went wrong.
Oops! Something went wrong.
While trying to add the title to your shelf something went wrong :( Kindly try again later!
Are you sure you want to remove the book from the shelf?
Oops! Something went wrong.
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
    Done
    Filters
    Reset
  • Discipline
      Discipline
      Clear All
      Discipline
  • Is Peer Reviewed
      Is Peer Reviewed
      Clear All
      Is Peer Reviewed
  • Item Type
      Item Type
      Clear All
      Item Type
  • Subject
      Subject
      Clear All
      Subject
  • Year
      Year
      Clear All
      From:
      -
      To:
  • More Filters
9 result(s) for "Prajapati, Dhirendra"
Sort by:
A Clustering Based Routing Heuristic for Last-Mile Logistics in Fresh Food E-Commerce
This study considers the fresh food city logistics that involves the last-mile distribution of commodities to the customer locations from the local distribution centres (LDCs) established by the e-commerce firms. In this scenario, the last-mile logistics is crucial for its speed of response and the effectiveness in distribution of packages to the target destinations. We propose a clustering-based routing heuristic (CRH) to manage the vehicle routing for the last-mile logistic operations of fresh food in e-commerce. CRH is a clustering algorithm that performs repetitive clustering of demand nodes until the nodes within each cluster become serviceable by a single vehicle. The computational complexity of the algorithm is reduced due to the downsizing of the network through clustering and, hence, produces an optimum feasible solution in less computational time. The algorithm performance was analysed using various operating scenarios and satisfactory results were obtained.
Meta-heuristic algorithms for solving the sustainable agro-food grain supply chain network design problem
Purpose Due to unceasing declination in environment, sustainable agro-food supply chains have become a topic of concern to business, government organizations and customers. The purpose of this study is to examine a problem associated with sustainable network design in context of Indian agro-food grain supply chain. Design/methodology/approach A mixed integer nonlinear programming (MINLP) model is suggested to apprehend the major complications related with two-echelon food grain supply chain along with sustainability aspects (carbon emissions). Genetic algorithm (GA) and quantum-based genetic algorithm (Q-GA), two meta-heuristic algorithms and LINGO 18 (traditional approach) are employed to establish the vehicle allocation and selection of orders set. Findings The model minimizes the total transportation cost and carbon emission tax in gathering food grains from farmers to the hubs and later to the selected demand points (warehouses). The simulated data are adopted to test and validate the suggested model. The computational experiments concede that the performance of LINGO is superior than meta-heuristic algorithms (GA and Q-GA) in terms of solution obtained, but there is trade-off with respect to computational time. Research limitations/implications In literature, inadequate study has been perceived on defining environmental sustainable issues connected with agro-food supply chain from farmer to final distribution centers. A MINLP model has been formulated as practical scenario for central part of India that captures all the major complexities to make the system more efficient. This study is regulated to agro-food Indian industries. Originality/value The suggested network design problem is an innovative approach to design distribution systems from farmers to the hubs and later to the selected warehouses. This study considerably assists the organizations to design their distribution network more efficiently.
Sustainable logistics network design for delivery operations with time horizons in B2B e-commerce platform
In the recent era, the rapidly increasing trend of e-commerce business creates opportunities for logistics service providers to grow globally. With this growth, the concern regarding the implementation of sustainability in logistic networks has received attention in recent years. Thus, in this work, we have focused on the vehicle routing problem (VRP) to deliver the products in a lesser time horizon with driver safety concern considerations in business (B2B) e-commerce platforms. We proposed a sustainable logistics network that captures the complexities of suppliers, retailers, and logistics service providers. A mixed-integer nonlinear programming (MINLP) approach is applied to formulate a model to minimize total time associated with order processing, handling, packaging, shipping, and vehicle maintenance. Branch-and-bound algorithms in the LINGO optimization tool and genetic algorithm (GA) are used to solve the formulated mathematical model. The computational experiments are performed in eight different case scenarios (small-sized problem to large-sized problem) to validate the model.
Sustainable Agro-Food Supply Chain in E-Commerce: Towards the Circular Economy
The continuous decline in the sustainable agro-food supply chain (AFSC) towards a Circular Economy (CE) has become a matter of great concern for the key stakeholders, including government organizations, businesses, end-users, and farmers. In line with this, the main purpose of this study is to develop a sustainable food Supply Chain Network (SCN). The SCN enables the collection of agro-food grains from different farmers’ locations and delivers the same to food processing units. To design an efficient and effective sustainable pickup and delivery network, a Mixed-Integer Non-Linear Programming (MINLP) mathematical model is formulated. The proposed model achieves the sustainability goal by minimizing the collection costs. The developed MINLP model is solved by using an exact optimization approach in LINGO 18 software. Further, to test the efficacy of the developed model, various computational experiments are performed, varying from small to large size data. The results of these experiments reflect that our model can support businesses in designing an efficient and effective sustainable pickup and delivery network. Lastly, it has been shown that innovative packaging materials can help to minimize the wastage of food.
An Internet of Things Embedded Sustainable Supply Chain Management of B2B E-Commerce
Adopting digital technologies in a business can help with sustainable supply chain management. These technologies can make e-commerce development faster and empower the emergence of B2B e-commerce businesses. In this study, our focus was to develop a framework for an Internet of things (IoT) embedded sustainable supply chain to deliver textile items using a B2B e-commerce business model. We formulated a mixed-integer non-linear programming (MINLP) model to minimize the total supply chain cost, including the B2B orders’ packaging, handling, and transportation, with carbon emission taxation. Furthermore, the purchasing cost of the RFID tags and IoT facilities that were provided on the transport vehicles was high. The proposed model was solved by using the global solver in the LINGO software package and finding the optimized value of the total supply chain network cost. We tested the proposed model in different case scenarios, i.e., small- to significant-sized problems. Then, a sensitivity analysis was performed to observe the variations in the overall cost of the supply chain network when there were changes in the main parameters of the proposed model. The results of the models showed that models can be helpful for efficient logistics planning and supply chain design.
Mapping and monitoring of glacier areal changes using multispectral and elevation data: A case study over Chhota-Shigri glacier
The Glacier studies are important for monitoring the hydrological cycle as well as the impact of climate change. Recent studies indicate that the glacier area-shrinking rate is accelerating specifically in the Himalayan glaciers. In this study, an integrated approach based on semi-automatic method has been used over the Chhota-Shigri glacier. The combination of multispectral (Landsat data from 1989 to 2015) and elevation data is used for delineation of glacier features. This comprehensive approach has integrated the remote sensing indices, thermal information and morphometric parameters generated using elevation data to delineate the glacier into three categories i.e. clean ice, ice mixed with debris (IMD) and debris. Results indicate that the areal extent of clean ice has significantly decreased whereas the IMD and debris cover area has increased from 1989 to 2015. The accuracy assessment is performed using a pan-sharpened image and field data. The overall accuracy obtained about 90.0% with a 0.895 kappa coefficient for the adopted approach. This glacier areal change information can be used for flow velocity measurements, hazard caused by glaciers, and the impact of climate change on glaciers.
Morphometric Parameters and Neotectonics of Kalyani River Basin, Ganga Plain: A Remote Sensing and GIS Approach
The drainage basin of the Kalyani river, a tributary of Gomati river has been mapped and delineated using Survey of India toposheets (1:50,000 scale) and remote sensing satellite data. The digitization, slope map preparation and statistical calculations have been carried out with the help of geographical information system (Arc GIS 10). Kalyani a fifth order river exhibits meandering behavior having 2.45 sinuosity index (SI). The Kalyani river basin has about 1235 km 2 area with NW-SE sloping trend. The total number of first, second, third, and fourth order streams are 373, 71, 12 and 2 respectively, showing dominance of first order streams in the basin. The mean bifurcation ratio (Rb) of the entire basin is 4.8, which indicates that the drainage is not much influenced by geological structures and exhibits dendritic drainage pattern. Relief ratio (Rr) indicates low to medium surface run-off, and low stream power for erosion. The analysis of river bank height ‘r’ (escarpment) and longitudinal profile of the river closely reveals neotectonic activity at some locations in the basin. To prepare a comprehensive watershed development and management plan, it is important to understand the topography and drainage characteristics of the region.
Climatically induced levee break and flood risk management of the Gorakhpur region, Rapti River basin, Ganga Plain, India
A densely populated city, Gorakhpur, located on the bank of Rapti river in the Ganga plain, is frequently affected by flooding. The Rapti river exhibits narrow channel within wide valley, channel bars, natural levee and river terraces. Artificial levees are constructed in the valley during low discharge period to mitigate the flood and also to provide the additional land to the society. These levees break during prolonged heavy rain and induce the catastrophic flood because it is not constructed by analyzing the capacity of the bracketed channel to accommodate the high discharge of the river. The precipitation, discharge, sediment load, and river water levels are correlated by making graphs between these parameters to analyze and identify the threshold limits and main reasons for flood. It explains that discharge and sediment load increases with precipitation during monsoon season, whereas the water storage capacity of the river decreases due to siltation and artificial levee. Hence, during heavy rain in this region, water rises in the channel, which either overtops the bank or breaks the levee and creates the flood. Flood inundation map was prepared using GIS techniques from 70 m base level to 81.5 m high level, which indicate the inundated area with every 1-2.5 m rise in the Rapti river water level. Rating curves and flood frequency curves have been prepared to identify the recurrence interval for major floods. It is concluded that prolong heavy precipitation, discharge variability of the river, siltation in the river bed, artificial levee, and anthropogenic impacts on younger river terraces and river valley leads to flood. Its affect is devastating when water level, discharge and sediment loads are above 77 m, 5000 m3/sec, and 5 metric tones respectively. The flood inundation map and recurrence interval are useful parameters for flood risk management, whereas the upland terrace is flood-free surface suitable for settlement. This study can be used as a model for other flood prone regions.
Morphometric parameters and neotectorphometric parameters and neotectonics of Kalyani River basin, Ganga Plain; a remote sensing and GIS approach
The drainage basin of the Kalyani river, a tributary of Gomati river has been mapped and delineated using Survey of India toposheets (1:50,000 scale) and remote sensing satellite data. The digitization, slope map preparation and statistical calculations have been carried out with the help of geographical information system (Arc GIS 10). Kalyani a fifth order river exhibits meandering behavior having 2.45 sinuosity index (SI). The Kalyani river basin has about 1235 km2area with NW-SE sloping trend. The total number of first, second, third, and fourth order streams are 373, 71, 12 and 2 respectively, showing dominance of first order streams in the basin. The mean bifurcation ratio (Rb) of the entire basin is 4.8, which indicates that the drainage is not much influenced by geological structures and exhibits dendritic drainage pattern. Relief ratio (Rr) indicates low to medium surface run-off, and low stream power for erosion. The analysis of river bank height 'r' (escarpment) and longitudinal profile of the river closely reveals neotectonic activity at some locations in the basin. To prepare a comprehensive watershed development and management plan, it is important to understand the topography and drainage characteristics of the region.