Ayala, R., Mula, J., Poler, R., Díaz-Madroñero, M. (2024). A proposal of analytical formulations to calculate safety lead times under demand variability. A case study. Ain Shams Engineering Journal, 15(9), 102902.

Cañas, H., Mula, J., Campuzano-Bolarin, F. (2024). Strategical and tactical supply chain optimisation for smart production planning and control 4.0. International Journal of Production Research, 1-21.

Serrano-Ruiz, J.C., Mula, J., Poler, R., Díaz-Madroñero, M. (2024). Smart master production scheduling by deep reinforcement learning: an exploratory analysis. IFIP Advances in Information and Communication Technology, 727, 228-244.

Serrano-Ruiz, J.C., Ferreira, J., Jardim-Goncalves, R., Ortiz, A. (2024). Relational network of innovation ecosystems generated by digital innovation hubs: a conceptual framework for the interaction processes of DIHs from the perspective of collaboration within and between their relationship levels. Journal of Intelligent Manufacturing.

Quintero, M., Mula, J., Campuzano-Bolarín, F. (2024). A conceptual framework for sustainable freight land transport simulation – Part 1. International Journal of Simulation Modelling, 23(3), 389-400.

Andres, B., Diaz-Madroñero, M., Soares, A. L., Poler, R. (2024). Enabling Technologies to Support Supply Chain Logistics 5.0. IEEE Access, 12, 43889-43906.

Ghorbani, E., Gomez, J. F., Panadero, J., Juan, A. A. (2024). A sim-learnheuristic algorithm for solving a capacitated dispersion problem under stochastic and non-static conditions. AIMS Mathematics, 9(9), 24247-24270.

Bussieweke, F., Mula, J., Campuzano-Bolarin, F. (2024). Optimisation of recovery policies in the era of supply chain disruptions: a system dynamics and reinforcement learning approach. International Journal of Production Research, 1-25.

Martin, X.A., Escoto, M., Guerrero, A., Juan, A. A. (2024). Battery management in electric vehicle routing problems: a review. Energies, 17(5), 1141.

Peidro, D., Martin, X.A., Panadero, J., Juan, A. A. (2024). Solving the uncapacitated facility location problem under uncertainty: a hybrid tabu search with path-relinking simheuristic approach. Applied Intelligence, 54, 5617-5638.

Aldás, D., Mula, J., Díaz-Madroñero, M. (2024). Dimensions and challenges to integrate operations strategies into a sustainable and circular supply chain. Lecture Notes on Data Engineering and Communications Technologies, 206, 403-408.

Becerra, P., Mula, J., Sanchis, R. (2024). An overview of shoring decisions for sustainable and resilient supply chains from a quantitative modelling perspective. Lecture Notes on Data Engineering and Communications Technologies, 206, 397-402.

Fateh, A., Mula, J., Diaz-Madroñero, M. (2024). An overview on optimisation and big data in supply chain 4.0. Lecture Notes on Data Engineering and Communications Technologies, 206, 507-513.

Guerrero, B., Mula, J., Poler, R. (2024). Sustainable operations management towards Industry 5.0. Lecture Notes on Data Engineering and Communications Technologies, 206, 243-247.

Moreno, J., Mula, J., Poler, R. (2024). Trends and future research into the integration of procurement transportation and inventory decisions. Lecture Notes on Data Engineering and Communications Technologies, 206, 270-275.

Mula, J., Sanchis, R., De la Torre, R., Becerra, P. (2024). Simulation and improvement of transshipment decisions in a fast-fashion retail network. Lecture Notes on Data Engineering and Communications Technologies, 206, 495-500.

Ponce, E., Mula, J., Peidro, D. (2024). Analysis of blockchain applications in the supply chain field. Lecture Notes on Data Engineering and Communications Technologies, 206, 264-269.

Reyes, J., Mula, J., Díaz-Madroñero, M., Andres, B. (2024). Normalised data model for cloud collaborative manufacturing: applied to the footwear industry. Lecture Notes on Data Engineering and Communications Technologies, 206, 409-414.

Rojas, T., Mula, J., Sanchis, R. (2024). Quantitative models for printing production planning in a lean manufacturing approach under uncertainty. Lecture Notes on Data Engineering and Communications Technologies, 206, 253-263.

Serrano-Ruiz, J.C., Mula, J., Poler, R. (2022). Interoperability as a supporting principle of Industry 4.0 for smart manufacturing scheduling: A research note. Enterprise Interoperability X. Proceedings of the I-ESA Conferences, 11, 183-193.

Serrano-Ruiz, J.C., Mula, J., Poler, R. (2024). Job shop smart manufacturing scheduling by deep reinforcement learning. Journal of Industrial Information Integration, 38, 100582.

Reyes, J., Mula, J., Diaz-Madroñero, M. (2024). Quantitative insights into the integrated push and pull production problem for lean supply chain planning 4.0. International Journal of Production Research, 62(17), 6251-6275.

Neroni M., Bertolini M., Juan, A. A. (2024). A biased-randomized discrete event algorithm to improve the productivity of automated storage and retrieval systems in the steel industry. Algorithms, 17(1), 46.

Lorente-Leyva, Leandro L., Alemany, M. M. E., Peluffo-Ordóñez, Diego H. (2024). A conceptual framework for the operations planning of the textile supply chains: Insights for sustainable and smart planning in uncertain and dynamic contexts. Computers & Industrial Engineering, 187, 109824.

Becerra, P., Mula, J., Sanchis, R., Campuzano-Bolarin, F. (2024). Simulation optimisation of a sustainable copper mining closed-loop supply chain. International Journal of Systems Science: Operations and Logistics, 11(1).

Juan, A.A., Rabe, M., Ammouriova, M., Panadero, J., Peidro, D., Riera, D. (2023). Solving NP-hard challenges in logistics and transportation under general uncertainty scenarios using fuzzy simheuristics. Algorithms, 16(12), 570.

Castaneda, J., Herrera, E.M., Londoño, J.C., Panadero, J., Juan, A.A. (2023). Using heuristics to enhance real-life warehouse replenishment processes in the fashion industry. Transportation Research Procedia, 71, 124-131.

Gomez J. F., Uguina A. R., Panadero J., Juan, A. A. (2023). A learnheuristic algorithm for the capacitated dispersion problem under dynamic conditions. Algorithms, 16(12), 532.

Rojas, T., Mula, J., Sanchis, R. (2023). Quantitative modelling approaches for lean manufacturing under uncertainty. International Journal of Production Research, 62(16), 5989-6015.

Perez-Gosende, P., Mula, J., Diaz-Madroñero, M. (2023). A conceptual framework for multi-objective facility layout planning by a bottom-up approach. International Journal of Production Management and Engineering 11(1), 1-16.

Rojas, T., Mula, J., Sanchis, R. (2023). A conceptual framework for lean manufacturing under uncertainty conditions in the graphic industry. Lecture Notes on Data Engineering and Communications Technology, 160, 501-506.

Guzman, E., Poler, R., Andres, B. (2023) A matheuristic approach combining genetic algorithm and mixed integer linear programming model for production and distribution planning in the supply chain. Advances in Production Engineering & Management, 18(1), 19-31.

Pérez-Cubero, E., Poler, R. (2023). Conceptual proposal for the design of a work order prioritization heuristic in a workshop. Lecture Notes on Data Engineering and Communications Technology, 160, 179-184.

Serrano-Ruiz, J. C., Mula, J., Poler, R. (2023). Deep reinforcement learning for the job shop scheduling problem: reference axes for modelling, implementation and validation. Lecture Notes on Data Engineering and Communications Technology, 160, 93-100.

Pérez-Gosende, P., Mula, J., Díaz-Madroñero, M. (2023). A bottom-up multi-objective optimisation approach to dynamic facility layout planning. International Journal of Production Research, 62(3), 626-643.

Martin, X. A., Hatami, S., Calvet, L., Peyman, M., Juan, A. A. (2023). Dynamic reactive assignment of tasks in real-time automated guided vehicle environments with potential interruptions. Applied Sciences, 13(6), 3708.

Becerra, P., Mula, J., Sanchis, R. (2023). Mathematical programming models for sustainable inventory management in a supply chain. Lecture Notes on Data Engineering and Communications Technology, 160, 152-157.

Reyes, J., Mula, J., Díaz-Madroñero, M. (2023). Optimisation modeling for lean, resilient, flexible and sustainable supply chain planning. Lecture Notes on Data Engineering and Communications Technology, 160, 341-345.

Tarazona, M., Mula, J., Poler, R. (2023). Optimisation of production scheduling and sequencing problems in industry 4.0. Lecture Notes on Data Engineering and Communications Technology, 160, 107-112.

Becerra, P., Mula, J., Sanchis, R. (2023). Optimising location, inventory and transportation in a sustainable closed-loop supply chain. International Journal of Production Research, 62(5), 1609-1632.

Ghorbani, E., Fluechter, T., Calvet, L., Ammouriova, M., Panadero, J., Juan, A. A. (2023). Optimizing energy consumption in smart cities’ mobility: electric vehicles, algorithms, and collaborative Economy. Energies, 16 (3), 1268.

Perez-Gosende, P., Mula, J., Diaz-Madroñero, M. (2023). Reference optimisation models for facility layout planing in the metal-mechanic industry. Lecture Notes on Data Engineering and Communications Technology, 160, 482-487.

Martin, X. A., Panadero, J., Peidro, D., Perez‐Bernabeu, E., Juan, A. A. (2023). Solving the time capacitated arc routing problem under fuzzy and stochastic travel and service times. Networks, 82, 318-335.

Aldás, D., Mula, J., Díaz-Madroñero, M. (2023). Theoretical advances in the supply chain operations strategy with a circular economy approach. Lecture Notes on Data Engineering and Communications Technology, 160, 494-500.

Cañas, H., Mula, J., Campuzano-Bolarin, F., Poler, R. (2022). A conceptual framework for smart production planning and control in Industry 4.0. Computers & Industrial Engineering, 173, 108659.

Guzman, E., Andres, B., Poler, R. (2022). A decision-making tool for algorithm selection based on a fuzzy TOPSIS approach to solve replenishment, production and distribution planning problems. Mathematics, 10 (9), 1544.

Gomez, J. F., Panadero, J., Tordecilla, R. D., Castaneda, J., Juan, A. A. (2022). A multi-start biased-randomized algorithm for the capacitated dispersion problem. Mathematics, 10(14), 2405.

Serrano-Ruiz, J. C., Poler, R., Mula, J. (2022). A simpy digital twin job shop for learning in industrial engineering and logistics. INTED2022 Proceedings, 2325-2334.

Castaneda, J., Neroni, M., Ammouriova, M., Panadero, J., Juan, A. A. (2022). Biased-randomized discrete-event heuristics for dynamic optimization with time dependencies and synchronization. Algorithms, 15(8), 289.

Herrera, E. M., Panadero, J., Carracedo, P., Juan, A. A., Perez-Bernabeu, E. (2022). Determining reliable solutions for the team orienteering problem with probabilistic delays. Mathematics, 10(20), 3788.

Serrano-Ruiz, J. C., Mula, J., Poler, R. (2022). Development of a multidimensional conceptual model for job shop smart manufacturing scheduling from the Industry 4.0 perspective. Journal of Manufacturing Systems, 63, 185-202.

Castaneda, J., Ghorbani, E., Ammouriova, M., Panadero, J., Juan, A. A. (2022). Optimizing transport logistics under uncertainty with simheuristics: concepts, review and trends. Logistics, 6(3), 42.

Esteso, A., Peidro, D., Mula, J., Díaz-Madroñero, M. (2022). Reinforcement learning applied to production planning and control. International Journal of Production Research, 1-18.

Ammouriova, M., Herrera, E. M., Neroni, M., Juan, A. A., Faulin, J. (2022). Solving vehicle routing problems under uncertainty and in dynamic scenarios: from simheuristics to agile optimization. Applied Sciences, 13(1), 101.

Becerra, P., Mula, J., Sanchis, R. (2022). Sustainable inventory management in supply chains: trends and further research. Sustainability, 14(5), 2613.

Serrano-Ruiz, J. C., Mula, J., Poler, R. (2022). Toward smart manufacturing scheduling from an ontological approach of job-shop uncertainty sources. IFAC-PapersOnLine, 55(2), 150-155.

Congresos

Mula, J. (2023). Optimisation systems in the Industry 4.0 era. 29th IJCIEOM – International Joint Conference on Industrial Engineering and Operations Management. Lisbon, Portugal. https://ijcieom.org/2023/?page_id=148

Tesis doctorales

Reyes Vásquez, J.P. (2024). Conceptual and optimisation modelling for lean supply chain planning in Industry 4.0. [Tesis doctoral]. Universitat Politècnica de València.

Serrano-Ruiz, J.C. (2023). Job shop smart manufacturing scheduling by deep reinforcement learning for Industry 4.0 [Tesis doctoral]. Universitat Politècnica de València.

Cañas Sánchez, H.E. (2023). Models, algorithms and digital technologies for the automation and collaboration of connected smart factories in an industry 4.0 environment [Tesis doctoral]. Universitat Politècnica de València.

Becerra, P. (2023). Quantitative models of location, inventory and transportation decisions for sustainable supply chain management [Tesis doctoral]. Universitat Politècnica de València.

Pérez Gosende, P.A. (2022). Enfoque multiobjetivo bottom-up para la planificación dinámica de la distribución espacial en plantas industriales [Tesis doctoral]. Universitat Politècnica de València.

Trabajos fin de grado

Cavero Merino, J.V. (2023). Diseño e Implementación de una Herramienta de Optimización para la Gestión del Beneficio en una Empresa del Sector Metalmecánico [Trabajo fin de grado]. Universitat Politècnica de València.