An Integrated Model for Parallel Machine Scheduling and Heterogeneous Fleet Vehicle Routing Problem with Earliness and Tardiness Penalties

This study investigates an integrated production scheduling and distribution routing problem in which customer orders are first processed on parallel machines and subsequently delivered to customers by a heterogeneous fleet of vehicles. Compared with classical models, the proposed model is extended in the following aspects: (۱) heterogeneity in vehicle capacities and usage costs, (۲) consideration of order unloading time at customer locations, (۳) inclusion of earliness and tardiness penalties related to delivery times, and (۴) incorporation of production machine usage costs. The objective of the model is to minimize the total system costs, including production, transportation, and time-related penalty costs. To solve the problem, a mixed-integer linear programming (MILP) model is developed, and small-sized instances are solved using the CPLEX solver. Given the high complexity of the problem, two metaheuristic algorithms, namely tabu search and simulated annealing, are proposed to solve medium- and large-scale instances. The computational results indicate that the metaheuristic approaches are capable of solving large-scale problems within reasonable computational times, and that tabu search outperforms simulated annealing in terms of solution quality.

Keywords:

Production scheduling , Vehicle routing , Heterogeneous fleet , Mixed-integer linear programming