Supply and Demand Selection Problems in Supply Chain Planning

Mohammadivojdan, Roshanak; Geunes, Joseph

doi:10.1007/978-3-319-99142-9_5

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…Proposed solution algorithms outperform commercial solvers, and the paper provides managerial insights on the impact of risk aversion, the number of products, and market pool size. Mohammadivojdan and Geunes (2018) discuss various supply chain planning problems that arise when multiple demand sources are available. The first problem pertains to selecting a subset of available demand sources to maximize profit or minimize cost.…”

Section: Market and Demand Selection In The Supply Chainmentioning

confidence: 99%

Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection

Aal

2024

10.5267/j.ijiec

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It is crucial to identify alternative energy sources owing to the ever-increasing demand for energy and the other environmental problems associated with using fossil fuels. Biomass as a source of bioenergy is considered a promising alternative to fossil fuels. This study aims to optimize the biomass supply chain by developing an integrated model incorporating typical tactical supply chain decisions based on market or demand selection decisions. To this end, a novel mixed-integer linear programming (MILP) model is proposed to maximize the profit of the corresponding biomass supply chain and to commercialize electricity production by selecting electricity demand and making supply chain decisions regarding power plant operations, biomass feedstock purchase and storage, and biomass transport trucks. Owing to the intricacy of the MILP model, a fix-and-optimize-based solution strategy is developed and validated by applying it to several instances of a real-world case study. The results demonstrate that the proposed strategy can significantly reduce computational time while preserving high solution quality. Additionally, it helps improve planning and decision-making as it reveals the effect of essential biomass logistics characteristics on routing outcomes.

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Section: Market and Demand Selection In The Supply Chainmentioning

confidence: 99%

Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection

Aal

2024

10.5267/j.ijiec

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“…The farmer will need to choose which products they are willing to farm. In this work, we employ a genetic algorithm to tackle this decision-making problem referred to as the demand selection problem (Geunes et al, 2005;Mohammadivojdan and Geunes, 2018). Although this model is developed to assist farmers in demand selection and to plan their farming schedule, this approach can be generalised to any field that requires demand selection and a division of the work resources.…”

Section: Optimization Approachmentioning

confidence: 99%

An asexual genetic algorithm for the smallholders’ demand selection problem

2023

Proceedings of the 9th International Food Operations and Processing Simulation Workshop

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As food safety shakes due to climate change and the looming possibility of a calamity similar to that of the COVID-19 pandemic, along with the increase in the world's population, there is an immediate need to increase food production by optimizing the agri-food supply chain. This work aims to help small-scale farmers manage this increase in orders and help them gear their resources towards more profitable practices by employing a multi-objective optimization model based on genetic algorithms that considers environmental aspects. To do so, we implement an asexual genetic algorithm that takes as input the demands received by the farmer and outputs the best combinations of demands to meet. The model takes into consideration the amount of land available for cultivation, as well as the resources (water, cost of cultivation, etc.) and revenue of the demands to determine the best combinations of demands to meet. This work is developed in the SMALLDERS framework and builds over the scarce literature that tackled the demand selection problem in the agricultural field.

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Supply and Demand Selection Problems in Supply Chain Planning

Cited by 2 publications

References 18 publications

Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection

Matheuristic approach and a mixed-integer linear programming model for biomass supply chain optimization with demand selection

An asexual genetic algorithm for the smallholders’ demand selection problem

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