Genetic Algorithm Based Inventory Optimization Analysis in Supply Chain Management

Radhakrishnan, P.; Prasad, V. M.; Gopalan, M.

doi:10.1109/iadcc.2009.4809047

Cited by 14 publications

(8 citation statements)

References 12 publications

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“…The application of optimization techniques, including linear programming, genetic algorithms, and tabu search, is a key contribution of this study, which is in line with previous studies such as Jauhar and Pant (2016), Min (2015), Sang (2021), and Radhakrishnan et al (2009) [43][44][45][46]. However, this study underscores these techniques' potential to augment both the efficiency and sustainability of the logistical process involved in residual biomass collection.…”

Section: Literature Reviewsupporting

confidence: 78%

Optimization of the Residual Biomass Supply Chain: Process Characterization and Cost Analysis

Nunes

Silva

2023

Logistics

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This study delves into the critical role of logistical cost optimization in the residual woody biomass supply chain, aiming to enhance the sustainability and efficiency of this resource’s exploitation. The research underscores that proficient cost management of logistical operations is pivotal for the economic feasibility of residual biomass utilization. The paper scrutinizes key aspects, such as collection, transportation, storage, and processing of biomass, emphasizing their individual contributions to the overall cost. It also pays particular attention to the impacts of seasonality and biomass quality variations, which directly influence the cost and effectiveness of the supply chain. To facilitate a deeper understanding of these factors, the study introduces mathematical models that enable the exploration of diverse scenarios and optimization strategies. The use of linear programming, genetic algorithms, and tabu search techniques are discussed in the context of these models. The findings of this research hold significant implications for the management of the residual biomass supply chain and contribute to the transition towards a low-carbon economy.

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Section: Literature Reviewsupporting

confidence: 78%

Optimization of the Residual Biomass Supply Chain: Process Characterization and Cost Analysis

Nunes

Silva

2023

Logistics

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“…The application of the two-stage genetic algorithm extends beyond groupage delivery and can be adapted to various optimization scenarios in transportation and logistics. For instance, in inventory management 75 , the algorithm can optimize warehouse locations and inventory allocation to minimize storage costs and meet demand fluctuations effectively.…”

Section: Utilization Efficiencymentioning

confidence: 99%

Two-Stage Genetic Algorhitm for Optimization Logistics Network for Groupage Delivery

Malashin,

Tynchenko,

Masich

et al. 2024

Preprint

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This study explores groupage delivery optimization through a two-stage GA framework. The goal of optimization is to define locations of regional branch warehouses of Logistics Network to reduce transportation costs. The first stage of the GA focuses on identifying branch warehouses from a list of cities and uses the standard binary string approach, while the second stage solves Vehicle Routing Problem (VRP) using combinatorial GA. This research contributes to advancing logistics optimization methodologies and provides valuable insights for solving Location Routing Problem (LRP) which entails two problems: the Facility Location Problem (FLP) and the Multiple Vehicle Routing Problem (MVRP).

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“…A search heuristic inspired by the process of natural selection. It's used to find approximate solutions to optimization and search problems [23,24,25,26].…”

Section: Genetic Algorithmmentioning

confidence: 99%

Enhanced Supply Chain Algorithm for ERP Systems Using ACO, Genetic, and Floyd-Warshall Algorithms

Aslam

2023

JERR

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In the era of digital transformation, optimizing supply chains is paramount for businesses to remain competitive. This research article delves into the creation of an enhanced supply chain algorithm for ERP systems using the Ant Colony Optimization (ACO), Genetic, and Floyd-Warshall algorithms. Through a comparative analysis using dummy data from two companies, Alco and Palto, we demonstrate the efficacy of our approach.

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Genetic Algorithm Based Inventory Optimization Analysis in Supply Chain Management

Cited by 14 publications

References 12 publications

Optimization of the Residual Biomass Supply Chain: Process Characterization and Cost Analysis

Optimization of the Residual Biomass Supply Chain: Process Characterization and Cost Analysis

Two-Stage Genetic Algorhitm for Optimization Logistics Network for Groupage Delivery

Enhanced Supply Chain Algorithm for ERP Systems Using ACO, Genetic, and Floyd-Warshall Algorithms

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