Browsing by Author "Mogale, D. G."

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    Designing a food supply chain for enhanced social sustainability in developing countries
    (Taylor & Francis, 2022-05-27) Mogale, D. G.; Ghadge, Abhijeet; Cheikhrouhou, Naoufel; Tiwari, Manoj Kumar
    The food grain production in India has progressively risen in the past few decades, whereas the storage capacity has remained limited. The policymakers in India are attempting to close this capacity gap while addressing sustainability objectives. However, the quantification and integration of multiple social sustainability factors have remained a challenge. To improve the overall sustainability, the study attempts to develop a mathematical model considering procurement, transportation, inventory, and location-related issues. Several supply chain network factors are integrated and assessed while focussing on the social sustainability dimension. Three cases of India's largest food grain-producing and consuming states are analysed with the help of two Pareto-based algorithms. Multiple relationships between variations in supply, demand, and the capacity of silos with three defined objectives are evaluated. It is observed that, the demand significantly influences the economic and environmental objectives compared with the supply and silo capacity. The capacity of silos has a more significant impact on social objectives than economic and environmental objectives. Results reveal the importance of establishing a sufficient number of modernised silos, which reduces environmental impact and improves social factors such as farmers’ economic condition and welfare, balanced economic development, number of jobs created, and public health level.
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    Designing a sustainable freight transportation network with cross-docks
    (Taylor & Francis, 2022-02-22) Mogale, D. G.; De, Arijit; Ghadge, Abhijeet; Kumar Tiwari, Manoj
    This study aims to develop a sustainable freight transportation network considering capacitated cross-docks for minimising the overall supply chain costs, including carbon emission cost. The problem is inspired by a major retail company based in India, which would like to expand its product portfolio in the new region. A mathematical model is developed to minimise total costs encompassing transportation cost, pipeline and retailers inventory cost, fixed cost of cross-dock and carbon emission costs. The deterministic time dependant demand, multiple products and multiple sourcing and distribution are some of the challenges faced by the retail industry. A two-level self-adaptive variable neighbourhood search algorithm is applied to solve a computationally complex problem. The results based on a two-level self-adaptive variable neighbourhood search algorithm are compared with the variable neighbourhood search algorithm to test the robustness of the developed model. Results reveal that an increase in retailers over suppliers significantly influences the number of open cross-docks. A multiple-case scenario approach captures the implications of varying capacity on the number of open cross-docks; thus, supporting the freight distribution managers in making sustainability-driven decisions.
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    Modelling supply chain network for procurement of food grains in India
    (Taylor and Francis, 2019-10-24) Mogale, D. G.; Ghadge, Abhijeet; Kumar, Sri Krishna; Tiwari, Manoj Kumar
    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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    Multi-objective modelling of sustainable closed-loop supply chain network with price-sensitive demand and consumer’s incentives
    (Elsevier, 2022-03-31) Mogale, D. G.; De, Arijit; Ghadge, Abhijeet; Aktas, Emel
    Closed-loop supply chains (CLSCs) are essential for maximising the value creation over the entire life cycle of a product. The design of these networks is increasing due to growing online businesses and rising sustainability awareness. This study develops a multi-objective optimisation model for sustainable CLSC network problem considering supply chain’s inherent complexity (multi-echelon, multi-product, multi-mode and multi-period nature) along with price-sensitive demand, consumer’s incentives and different quality levels of product. The proposed model seeks to optimise total cost and carbon emissions generated by production, distribution, transportation, and disposal activities. A two-stage algorithm, through the integration of the Non-Dominated Sorting Genetic Algorithm (NSGA-II) and Co-Kriging approach is utilised to determine the trade-off between costs and carbon emissions in the CLSC network. Data collected from a leading European household appliance company was used to analyse and interpret the developed model. The results show that the proposed two-stage approach provides robust outcomes and is computationally less expensive than the epsilon constraint approach. The study evidences the positive effects of incentive pricing on returned goods in the reverse logistics network and provides multiple trade-off solutions for supply chain managers to make informed decisions.
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    Sustainability implementation challenges in food supply chains: a case of UK artisan cheese producers
    (Taylor and Francis, 2020-07-28) Ghadge, Abhijeet; Er Kara, Merve; Mogale, D. G.; Choudhary, Sonal; Dani, Samir
    Food supply chains are receiving increased attention due to rapid depletion of natural resources, increasing quality standards and rising food safety and security concerns. Implementing sustainability practices in food supply chains is believed to overcome such emerging challenges. However, limited studies address sustainability implementation concerns, particularly in cold food supply chains. Thus, this study attempts to identify factors hindering sustainability implementation in cold food chain networks by considering a case of UK artisan cheese producers. Survey data is utilised to identify and prioritise barriers for implementing sustainability following fuzzy analytic hierarchy process and sensitivity analysis. The analysis identified several key barriers, including initial investment cost, firm size and unawareness of government regulations. The internal barriers significantly dominate the implementation of sustainability practices in comparison to external barriers. Lack of consensus regarding the concept of sustainability by different stakeholders is observed to be an issue negatively affecting the level of integration in SMEs. Findings will help food and dairy SME's in gaining competitive advantage through the successful implementation of sustainability practices.