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A new approach of linking mathematical optimization and discrete-event simulation for operating transshipment terminals in the parcel delivery industry

: Diekmann, Daniel; Baudach, Jens; Clausen, Uwe

European Multidisciplinary Society for Modelling and Simulation Technology -EUROSIS-; Departamento de Engenharia Civil, Faculdade de Engenharia da Universidade do Porto -FEUP-:
28th European Simulation and Modelling Conference, ESM 2014 : October 22-24, 2014, FEUP - University of Porto, Portugal
Porto, 2014
European Simulation and Modelling Conference (ESM) <28, 2014, Porto>
Fraunhofer IML ()
logistics; parcel delivery industry; transshipment terminal; material flow discrete-event simulation; mathematical optimization

Mathematical optimization and discrete-event simulation represent two powerful methods that have been successfully used to solve a wide range of strategic, tactical and operational problems in logistics. The two methods, however, are mainly applied separately for different types of problems. The discrete-event simulation allows the modelling of logistics systems with almost unlimited complexity (including stochastic processes) very close to reality. However, finding the best system configuration is very difficult and time-consuming since there are many alternative scenarios that have to be evaluated. In contrast, mathematical optimization has the ability to make very complex decisions and find (near) optimal solutions. But real world logistic systems can only be solved on a less detailed Ievel without stochastic behaviour. In this paper we present first results of an ongoing research project which aims at developing a new solution approach that closely links the two methods optimization and simulation in an iterative way. As an almost ideal practical application, we use the tactical-operational planning of parcel transshipment terminals which contains a large number of decisions, such as (un)loading dock or sorting destination assignments, and considers complex automatic sorting systems as well as manual handling activities with many stochastic elements.