Version 1
: Received: 21 December 2022 / Approved: 23 December 2022 / Online: 23 December 2022 (01:39:06 CET)
How to cite:
Shokouhifar, M.; Sohrabi, M.; Rabbani, M.; Molana, M.; Werner, F. Designing a Renewable and Sustainable Phosphorus Fertilizer Supply Chain Network using an Ensemble Knowledge-based Heuristic-Metaheuristic Algorithm. Preprints2022, 2022120432. https://doi.org/10.20944/preprints202212.0432.v1
Shokouhifar, M.; Sohrabi, M.; Rabbani, M.; Molana, M.; Werner, F. Designing a Renewable and Sustainable Phosphorus Fertilizer Supply Chain Network using an Ensemble Knowledge-based Heuristic-Metaheuristic Algorithm. Preprints 2022, 2022120432. https://doi.org/10.20944/preprints202212.0432.v1
Shokouhifar, M.; Sohrabi, M.; Rabbani, M.; Molana, M.; Werner, F. Designing a Renewable and Sustainable Phosphorus Fertilizer Supply Chain Network using an Ensemble Knowledge-based Heuristic-Metaheuristic Algorithm. Preprints2022, 2022120432. https://doi.org/10.20944/preprints202212.0432.v1
APA Style
Shokouhifar, M., Sohrabi, M., Rabbani, M., Molana, M., & Werner, F. (2022). Designing a Renewable and Sustainable Phosphorus Fertilizer Supply Chain Network using an Ensemble Knowledge-based Heuristic-Metaheuristic Algorithm. Preprints. https://doi.org/10.20944/preprints202212.0432.v1
Chicago/Turabian Style
Shokouhifar, M., Mohammad Molana and Frank Werner. 2022 "Designing a Renewable and Sustainable Phosphorus Fertilizer Supply Chain Network using an Ensemble Knowledge-based Heuristic-Metaheuristic Algorithm" Preprints. https://doi.org/10.20944/preprints202212.0432.v1
Abstract
Phosphorus (P) is the most important substance in inorganic fertilizers used in agriculture industry. In this study, a multi-product and multi-objective model is presented considering economic and environmental concerns to design a renewable and sustainable P-fertilizer supply chain management (PFSCM). To handle complexities of the proposed model, an ensemble knowledge-based three-stage heuristic-metaheuristic algorithm utilizing heuristic information available in the model, whale optimization algorithm, and variable neighborhood search (named H-WOA-VNS) is proposed. At first, a problem-dependent heuristic is designed to generate a set of near-optimal feasible solutions. These solutions are fed into a population-based whale optimization algorithm which benefits from both exploration and exploitation strategies. Finally, a single-solution metaheuristic based on variable neighborhood search is applied to further improve the quality of the solution using local search operators. The objective function of the algorithm is formulated as a weighted average function to minimize total economic cost, while increasing crop yield and P use efficiency. Experimental results over five synthetic datasets and a real case study of the P-fertilizer supply chain confirm the superiority of the proposed method against the state-of-the-art techniques. The results demonstrate that the proposed method performs well in optimizing both the economic cost and environmental issues.
Engineering, Industrial and Manufacturing Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
