A imatheuristic approach combining genetic algorithm and mixed integer linear programming model for production and distribution planning in the supply chainGuzman, E. (Avtor) Poler, Raúl (Avtor) Andres, B. (Avtor) production and distribution planningsupplay chainmatheuristicgenetic algorithmmixed integer linear programming modelA number of research studies have addressed supply chain planning from various perspectives (strategical, tactical, operational) and demonstrated the advantages of integrating both production and distribution planning (PDP). The globalisation of supply chains and the fourth industrial revolution (Industry 4.0) mean that companies must be more agile and resilient to adapt to volatile demand, and to improve their relation with customers and suppliers. Hence the growing interest in coordinating production-distribution processes in supply chains. To deal with the new market’s requirements and to adapt business processes to industry’s regulations and changing conditions, more efforts should be made towards new methods that optimise PDP processes. This paper proposes a matheuristic approach for solving the PDP problem. Given the complexity of this problem, combining a genetic algorithm and a mixed integer linear programming model is proposed. The matheuristic algorithm was tested using the Coin-OR Branch & Cut open-source solver. The computational outcomes revealed that the presented matheuristic algorithm may be used to solve real sized problems. idance for large group enterprises to carry out centralized procurement management.Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering20232026-02-10 14:08:29Članek v reviji96991slContent from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.