@misc{11428,
  abstract     = {{Systems that place high demands on availability are typically modular in design. However, a modular design also offers potential for optimized operation under norma requirements. In this paper we present an approach to find optimal operating points from the characteristic fields of individual modules. Our approach consists of a two-step procedure. In the first stage, Pareto sets are calculated using the NSGA-II genetic algorithm. The second stage contains a heuristic that finds situationally optimal operating points using a defined operating strategy.}},
  author       = {{Lammersen, Maximilian and Rasche, Rainer}},
  booktitle    = {{Conference proceedings of Mecatronics & AISM 2023}},
  keywords     = {{modularity, optimization, PEBB, operating strategy, genetic algorithm, Pareto}},
  location     = {{Yokohama}},
  publisher    = {{*}},
  title        = {{{Optimized Operating Points for Power Electronic Building Blocks}}},
  year         = {{2023}},
}

@inproceedings{586,
  abstract     = {{Under the circumstance of advanced globalization, it is increasingly difficult for production companies to remain competitiveness. Many of them are forced to restrict budget and reduce production costs. In addition, the customization of product increases continuously. This results in extension of product variation and reduction of product life cycle. Therefore, the companies need a high flexibility to respond quickly to changes in the market and to customer requirements. Lean thinking, as a powerful tool, has been implemented by many companies in production and manufacturing. In order to avoid waste in lean manufacturing, it is necessary to manage efficiently the material flow. In this study, for a lean material handling system in the lean manufacturing of a company, an in-plant milk-run distribution system is taken into consideration. The system consistsof vehicles, which move periodically in certain routes. The materials are delivered in short intervals from a central storage area to several points of use in the production. By using milk-run in plant, the material handling processes can be standardized and therefore the waste can be eliminated. One additional aim of the study with milk-run distribution for the material provision is to minimize the handling time, which determines directly the personal costs. In order to realize the aim, the work has beendivided into several steps. At first, the production processes, especially the material provision for the production have been analyzed. Secondly, the technological solutions have been analyzed in order to handle different loading units required by different machines in the production. Thirdly, the milk-run distribution for lean production is formulated as an optimization problem with the object of minimizing the number of vehicles and the distance traveled under the constraints of specific time periods, capacity of vehicle and related stations etc. Fourthly, two optimization methods are developed in order to find the optimal solution for the milk-run problem and the performance of different methods is also compared.}},
  author       = {{Li, Li and Schulze, L.}},
  editor       = {{Villmer, Franz-Josef and Padoano, Elio}},
  isbn         = {{978-3-946856-00-9}},
  keywords     = {{Milk-Run, Material provision, Lean production, Genetic algorithm}},
  location     = {{Lemgo}},
  number       = {{1}},
  pages        = {{65--76}},
  title        = {{{In-Plant Milk-Run Distribution for Material Provision Optimization in Lean Production}}},
  year         = {{2016}},
}

@inproceedings{599,
  abstract     = {{Order picking has long been identified as the most labor costly and intensively activity in warehouse management. The orders from the customers need to be fulfilled tightly and timely. In order to keep the required high service level, the warehouse has to increase the picking productivity under the constraints of limited capacity. This paper concerns a man-togoods order picking system, in which the order pickers have to drive with a pallet jack to the storage locations. Considering that the orders are mostly small orders which consist of less lines, it is efficient to combine severalsingle customer orders into one picking order. Under this circumstance, this paper intends to answer the question of how customer orders should be grouped into picking orders with the aim of minimizing the total travel length through the warehouse. Consequently the productivity of the order picking system can be improved. An optimization problem for order batching is introduced. The optimization method of order batching is then proposed. Based on the simulation of different scenarios of incoming orders, it can be concluded that the developed method is effective in improving the productivity of the concerned order picking system.
}},
  author       = {{Li, Li and Schulze, L.}},
  booktitle    = {{Production Engineering and Management}},
  editor       = {{Padoano, Elio and Villmer, Franz-Josef}},
  isbn         = {{978-3-941645-11-0}},
  keywords     = {{Order picking, man-to-goods, order batching, picking productivity, genetic algorithm}},
  location     = {{Trieste, Italy}},
  number       = {{1}},
  pages        = {{319--326}},
  title        = {{{Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching}}},
  year         = {{2015}},
}