05.08.2022
Rückblick Konferenz MIM 2022 in Nantes
Vom 22. bis 24. Juni fand die 10. „IFAC Conference on Manufacturing Modelling, Management and Control” (MIM 2022) in Nantes (FR) statt. Auf der vom IMT Atlantique organisierten Konferenz tauschten sich Forschende über aktuelle Themen in den Bereichen Industrial Engineering, Supply Chain Management, Operations Research und weiteren verwandten Fachrichtungen aus. Neben der Vorstellung von 545 Konferenzbeiträgen wurden in 6 Keynotes spannende Einblicke in aktuelle Industrietrends gegeben.
Auf der Konferenz stellten Eduardo Alarcon und Julius Hoffmann 2 Beiträge unseres Lehrstuhls vor. Eduardo Alarcon präsentierte eine Arbeit zum Thema “Customer Order Scheduling in a Mobile 3D Printing Factory”, während Julius Hoffmann sich dem Thema „Iterated Greedy Algorithms for Customer Order Scheduling with Dedicated Machines“ widmete.
Customer Order Scheduling in a Mobile 3D Printing Factory
The problem addressed in this article is motivated by the development of small-scale, mobile factories equipped with 3D printing technologies. As they are embedded in standard containers, it is possible to move them from one location to another to support on-site and demand-driven production. To approach this problem, we developed a mixed-integer program model which defines the location of the mobile factory and assigns customer orders to each location and build, with the objective of minimizing relocation, transport, and tardiness costs. In addition, we proposed a heuristic method which, in an iterative process, builds a feasible solution and then seeks to improve it based on certain predefined rules. Early computational tests show that our algorithm achieves competitive results and can lay the groundwork for more sophisticated algorithms and problems.
Iterated Greedy Algorithms for Customer Order Scheduling with Dedicated Machines
The customer order scheduling problem has received much attention recently due to its relevance to real world applications. In this study, the minimization of the total completion time of customer orders is studied in a dedicated machine environment, i.e. each order consists of one job on each machine. Two iterated greedy algorithms are presented that make use of problem properties and apply a new local search as well as a new construction function. In a computational experiment, both algorithms outperform two state-of-the-art approaches and prove their suitability to solve the customer order scheduling problem with dedicated machines.
