Abstract
The management of the man–machine interaction is essential to achieve a competitive advantage among production firms and is more highlighted in the processing of agricultural products. The agricultural industry is underdeveloped and requires a transformation in technology. Advances in processing agricultural products (agri-product) are essential to achieve a smart production rate with good quality and to control waste. This research deals with modelling of a controllable production rate by a combination of the workforce and machines to minimize the total cost of production. The optimization of the carbon emission variable and management of the imperfection in processing makes the model eco-efficient. The perishability factor in the model is ignored due to the selection of a single sugar processing firm in the supply chain with a single vendor for the pragmatic application of the proposed research. A non-linear production model is developed to provide an economic benefit to the firms in terms of the minimum total cost with variable cycle time, workforce, machines, and plant production rate. A numerical experiment is performed by utilizing the data set of the agri-processing firm. A derivative free approach, i.e., algebraic approach, is utilized to find the best solution. The sensitivity analysis is performed to support the managers for the development of agricultural product supply chain management (Agri-SCM).
Highlights
Owing to the escalating awareness of resource depletion, climate change, and increasing population, firms in the agriculture domain need to redesign their current supply chain models by taking economic and environmental impacts into account [1]
The production rate of the system is depending upon the production rate of machines, which is kept in such a way that there are no shortages in the system
There are numerous techniques used to find the optimal solution of non-linear models e.g., interior point optimization (IPO), particle swarm optimization (PSO), pattern search (PS), genetic algorithm (GA), min-max optimization (MMO) etc
Summary
Owing to the escalating awareness of resource depletion, climate change, and increasing population, firms in the agriculture domain need to redesign their current supply chain models by taking economic and environmental impacts into account [1]. Replenishment strategies, product supply, and processing indicators are crucial to consider in the research models. Processes 2020, 8, 1505 meals, is growing due to changing lifestyles and overall decreasing tariffs. Owing to their common fragility and limited lifetime, handling those goods is far more complex and includes much higher risks compared to non-perishable products [2]. This work deals with the sugar processing from sugarcane as a raw material in local industry with outsourcing operation as a non-perishable product because of the long life of raw sugarcane. The supply chain considers a small portion of the whole network, i.e., a single sugar processing firm with a single outsourcing vendor
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