Mendoza, Abraham
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Preferred name
Mendoza, Abraham
Official Name
Mendoza Andrade, Abraham
Alternative Name
amendoza
Main Affiliation
ORCID
Scopus Author ID
56002690300
Researcher ID
V-4102-2018

Research Output

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CARE: Heuristics for two-stage multi-product inventory routing problems with replenishments

2016 , Ramkumar Nambirajan , Mendoza, Abraham , Subramanian Pazhani , T.T. Narendran , K. Ganesh

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Coordination of pricing and inventory replenishment decisions in a supply chain with multiple geographically dispersed retailers

2022 , Hamza Adeinat , Subramanian Pazhani , Mendoza, Abraham , Jose A. Ventura

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Multi-period multi-product closed loop supply chain network design: A relaxation approach

2021 , Subramanian Pazhani , Mendoza, Abraham , Ramkumar Nambirajan , T.T. Narendran , K. Ganesh , Olivares-Benitez, Elias

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A serial inventory system with supplier selection and order quantity allocation considering transportation costs

2016 , Subramanian Pazhani , José A. Ventura , Mendoza, Abraham

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CAR: heuristics for the inventory routing problem

2020 , Ramkumar Nambirajan , Mendoza, Abraham , Subramanian Pazhani , T. T. Narendran , K. Ganesh

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An application of interactive fuzzy optimization model for redesigning supply chain for resilience

2022 , Kanokporn Kungwalsong , Mendoza, Abraham , Vasanth Kamath , Subramanian Pazhani , Marmolejo Saucedo, José Antonio

AbstractSupply chain disruptions compel professionals all over the world to consider alternate strategies for addressing these issues and remaining profitable in the future. In this study, we considered a four-stage global supply chain and designed the network with the objectives of maximizing profit and minimizing disruption risk. We quantified and modeled disruption risk as a function of the geographic diversification of facilities called supply density (evaluated based on the interstage distance between nodes) to mitigate the risk caused by disruptions. Furthermore, we developed a bi-criteria mixed-integer linear programming model for designing the supply chain in order to maximize profit and supply density. We propose an interactive fuzzy optimization algorithm that generates efficient frontiers by systematically taking decision-maker inputs and solves the bi-criteria model problem in the context of a realistic example. We also conducted disruption analysis using a discrete set of disruption scenarios to determine the advantages of the network design from the bi-criteria model over the traditional profit maximization model. Our study demonstrates that the network design from the bi-criteria model has a 2% higher expected profit and a 2.2% lower profit variance under disruption than the traditional profit maximization solution. We envisage that this model will help firms evaluate the trade-offs between mitigation benefits and mitigation costs.

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Finding optimal dwell points for automated guided vehicles in general guide-path layouts

2015 , José A. Ventura , Subramanian Pazhani , Mendoza, Abraham

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