Yağmur, E.Kesen, S.E.2023-11-112023-11-11202397830314361160302-9743https://doi.org/10.1007/978-3-031-43612-3_27https://hdl.handle.net/20.500.13091/4768Proceedings of the 14th International Conferences on Computational Logistics, ICCL 2023 -- 6 September 2023 through 8 September 2023 -- -- 300429The operational integration of the production and distribution activities in a supply chain requires concurrent consideration of two major problems known as production scheduling and vehicle routing. While the production environment of the integrated problem under study consists of identical parallel machines, the distribution environment has a limited number of homogeneous vehicles that deliver completed orders to customers. The objective function is to minimize the sum of total earliness and tardiness according to the time windows specified by each customer. In this paper, we first describe the integrated problem as a Mixed Integer Programming (MIP) model and subsequently present an Iterated Local Search (ILS) algorithm to find optimal or near-optimal solutions in a reasonable time. The performance of the ILS is evaluated against the MIP-based solutions obtained by applying a standard solver like CPLEX. According to the computational findings, the suggested ILS can find optimal or near optimal solutions for randomly generated test instances in just a few seconds. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.eninfo:eu-repo/semantics/closedAccessearlinessiterated local searchparallel machine schedulingtardinessvehicle routingInteger programmingLocal search (optimization)Optimal systemsProduction controlSupply chainsVehiclesEarlinessEarliness and tardinessIterated local searchNear-optimal solutionsOperational integrationParallel machines schedulingProduction environmentsProduction SchedulingProduction vehiclesTardinessVehicle routingConference Object10.1007/978-3-031-43612-3_272-s2.0-85172295160