Grain silo location-allocation problem with dwell time for optimization of food grain supply chain network

In the last few decades, production and procurement of food grain in India have steadily increased, however, storage capacity has not increased proportionally. The government of India (GOI) is establishing the various capacitated silos across the country to bridge this storage capacity gap. This paper presents a novel integrated multi-objective, multi-modal and multiperiod mathematical model for grain silo location-allocation problem with Dwell time to support the decision-making process of GOI. Two conflicting objectives- minimization of total supply chain network cost and total lead time (transit and dwell time) are simultaneously optimized using two Pareto based multi-objective algorithms with calibrated parameters

Grain silo location-allocation problem with dwell time for optimization of food grain supply chain network.

In the last few decades, production and procurement of food grain in India have steadily increased, however, storage capacity has not increased proportionally. The government of India (GOI) is establishing the various capacitated silos across the country to bridge this storage capacity gap. This paper presents a novel integrated multi-objective, multi-modal and multi-period mathematical model for grain silo location-allocation problem with Dwell time to support the decision-making process of GOI. Two conflicting objectives-minimization of total supply chain network cost and total lead time (transit and dwell time) are simultaneously optimized using two Pareto based multi-objective algorithms with calibrated parameters

Proceedings of the European Conference on Agricultural Engineering AgEng2021

This proceedings book results from the AgEng2021 Agricultural Engineering Conference under auspices of the European Society of Agricultural Engineers, held in an online format based on the University of Évora, Portugal, from 4 to 8 July 2021. This book contains the full papers of a selection of abstracts that were the base for the oral presentations and posters presented at the conference. Presentations were distributed in eleven thematic areas: Artificial Intelligence, data processing and management; Automation, robotics and sensor technology; Circular Economy; Education and Rural development; Energy and bioenergy; Integrated and sustainable Farming systems; New application technologies and mechanisation; Post-harvest technologies; Smart farming / Precision agriculture; Soil, land and water engineering; Sustainable production in Farm buildings

Book of abstracts, 4th World Congress on Agroforestry

International audienc

Modeling the contribution of ecological agriculture for climate change mitigation in cote d'Ivoire

The use of crop models is motivated by the prediction of crop production under climate change and for the evaluation of climate risk adaptation strategies. Therefore, in the present study the performance of DSSAT 4.6 was evaluated in a cropping system involving integrated soil fertility management options that are being promoted as ways of adapting agricultural systems to improve both crop yield and carbon sequestration on highly degraded soils encountered throughout middle Côte d’Ivoire. Experimental data encompassed two seasons in the Guinea savanna zone. Residues from the preceding vegetation were left to dry on plots like mulch on an experimental design that comprised the following treatments: (i) herbaceous savanna-maize, (ii)10 year-old of the shrub Chromolaena odorata fallow-maize (iii) 1 or 2 year-old Lalab pupureus stand-rotation, (iv) the legume L. pupureus -maize rotation; (v) continuous maize crop fertilized with urea; (vi) continuous maize crop fertilized with triple superphosphate; (vii) continuous maize crop, fertilized with both urea and triple superphosphate (TSP); (viii) continuous maize cultivation. The model’s sensitivity analysis was run to figure out how uncertainty of stable organic carbon (SOM3) can generate variation in the prediction of soil organic carbon (SOC) dynamics during the monitoring period of two years, within the first soil layer and to estimate the most suitable value. The observed variations were of 0.05 % in total SOC within the short-term and acceptable dynamics of changes were obtained for 0.80% of SOM3. The DSSAT model was calibrated using data from the 2007-2008 season and validated against independent data sets of yield of 2008-2009 to 2011-2012 cropping seasons. After the default values for SOM3 used in the model was substituted by the estimated one from sensitivity analysis, the model predicted average maize yields of 1 454 kg ha-1 across the sites versus an observed average value of 1 736 kg ha-1, R2 of 0.72 and RMSE of 597 kg ha-1. The impact of fallow residues and cropping sequence on maize yield was simulated and compared to conventional fertilizer and control data using historical climate scenarios over 12 years. Improving soil fertility through conservation agriculture cannot maintain grain yield in the same way as conventional urea inputs, although there is better yield stability against high climate variability according to our results