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Author: search.filters.author.Marmolejo-Saucedo, José AntonioHas files: No

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    Modeling responsible technologies using multiagent system for climate crisis and sustainability
    (Elsevier, 2025)
    Nanda, Pragyan
    ;
    Sahoo, Sipra
    ;
    Rodríguez Aguilar, Román  
    ;
    Marmolejo-Saucedo, José Antonio
    ;
    Behera, Itishree
    This chapter delves into the dynamic landscape of responsible technologies and their crucial role in addressing the climate crisis and advancing sustainability. It highlights the need to understand the intricate connections between technology adoption, environmental impact, and societal behavior across various dimensions of sustainability, including environmental, social, economic, cultural, technological, political, ethical, health, educational, and adaptive aspects. The chapter introduces the concept of responsible technologies and their key principles, emphasizing real-world experimentation limitations and simulation advantages, particularly through a multiagent system (MAS). It explores different modeling approaches, focusing on the suitability of MAS for studying responsible technologies, along with considerations in its implementation. A step-by-step guide is provided for constructing a tailored MAS model for responsible technologies, incorporating real-world data and environmental factors. Findings and insights from MAS simulations are analyzed, shedding light on the implications of responsible technology adoption across these sustainability dimensions. The chapter also underscores the pivotal role of a MAS in comprehensively modeling responsible technologies and invites further research exploration in this expansive domain, serving as a comprehensive guide for researchers, policymakers, and stakeholders committed to leveraging responsible technologies for climate change mitigation and sustainability advancement. ©The authors ©Elsevier.
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    Sales predictive analysis for improving supply chain drug sample
    (Elsevier BV, 2025)
    Téllez-Ballesteros, Susana Casy
    ;
    Torres-Mendoza, Ricardo
    ;
    Marmolejo-Saucedo, José Antonio
    ;
    Rodríguez Aguilar, Román  
    The delivery of drug samples allows increasing sales of pharmaceutical products [6]. However, we discovered some problems that can be improved in the supply chain that delivers drug samples (used for the treatment of excess glucose). Databases were integrated; then we apply data extraction and transformation; and finally we apply multiple regression analysis to explain drug sales. The first analysis evaluates the integration of regional data and the second analysis refers to data dis-aggregated by region. We identify the region with the greatest impact on sales and the impact of the delivery of drug samples in the Mexican market. ©The authors ©Elsevier ©Procedia Computer Science.
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    A Greenfield Analysis for Supply Chains Enhanced with Agent-Based Simulation
    (Springer, 2024-01-01)
    García-Roa, Eduardo
    ;
    Marmolejo-Saucedo, José Antonio
    ;
    Martínez, Ana Paula
    ;
    Elizarrarás, Fernando
    This chapter presents a strategy to improve the greenfield analysis of a supply chain. The proposed strategy is based on a multiparadigm simulation model that uses discrete event simulation and agent-based simulation for vehicles used in freight transport. The modeling was carried out using Anylogic software, which is the only software that allows the integration of different simulation methods in the same project. A hypothetical case study was developed to implement the strategy. © 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
      33  1
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    Resilience in Supply Chains: A Strategy Based on Inventory Policies
    (Springer, 2024-01-01)
    Eyssautier-Alvarado, Rodrigo
    ;
    Marmolejo-Saucedo, José Antonio
    ;
    García-Roa, Eduardo
    The resilience of supply chains is an increasingly important factor today. The effects of the COVID-19 pandemic have highlighted the importance of generating new strategies to reduce the risk of supply chain disruption. This paper proposes an inventory policy modeled in a simulation context. The case study is a hypothetical two-stage supply chain. The solution is given by the simulation of different scenarios where different data and policies are being taking into account to see different results and discard those policies that were not useful for this case study; all the simulations are made in anyLogistix software, which is a supply chain analytics software for designing and optimizing a supply chain. The results show the performance of the proposal in several disruption scenarios similar to those experienced in the COVID-19 pandemic. The solution proposal can serve as a reference in the functioning of supply chains in the post-COVID-19 era. ©Springer.
      23  2