Solving Logistics Scheduling Problems Using an Extended Many-Project Optimization Model

Logistics processes play an important role in the operation of production and service systems. The limited available resources of the systems are decisive from the point of view of efficient work. In today's globalized market environment, customer and client expectations are of prime importance. In order to fulfil their requirements, it is advisable to optimize the operation of the systems as much as possible. One of the suitable tools for this reason is the scheduling of activities. In our paper, we present an extended multi-project, multi-objective scheduling model that is suitable for the effective solution of scheduling problems in logistics systems. In the proposed model, logistics tasks appear as projects and the necessary resources are organized into types. Projects can have their own defined objective function system. The scheduler handles a set of projects that can include dependencies of projects. The objective function systems can involve different compositions and their importance can be specified individually. The limits of the resources can be given by an arbitrary discrete time function. The solution to the addressed scheduling problem is provided by a hybrid evolutionary search method using constructive heuristic algorithms. The quality of the solutions is determined using a multi-objective relative evaluation model. The paper demonstrates the applicability of the model through an illustrative example.