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• W4288826257 abstract "Abstract Driven by an increasing demand for individualized products and shorter product life-cycles, companies continuously extend their product portfolio. Simultaneously, companies expand into new markets to reach customers and to exploit varying location factors to reduce costs. Global production networks (GPNs) have to be adapted constantly to react to new circumstances and changes in the demand of products. To remain competitive, product allocation and production network configuration are essential. At the same time, companies face an increasing complexity while handling these tasks. This poses a challenge particularly for small and medium sized companies, which have limited planning capacities and management resources. Current literature describes optimization-based approaches for the integrated product allocation and network configuration of production networks. Yet, multi-objective models lack transparency of results and user friendliness. Therefore, this paper presents a multi-objective optimization model that incorporates flexibility and reconfiguration aspects to determine an optimal product allocation and network configuration of a GPN over a given planning horizon. The preemptive goal programming approach is used to identify Pareto-optimal solutions and to increase user friendliness. The subsequent verification, validation and post-optimality analysis combined in a structured process enables a wide range of companies to apply the approach. The model is successfully applied in the GPN of a special machine manufacturer, which produces high precision metrology machines. Due to its transparent approach for complex planning problems, the developed method provides a solid base for well-founded, objective decisions. Hence, the risk of costly errors in the planning phase is reduced." @default.
• W4288826257 created "2022-07-30" @default.
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• W4288826257 date "2022-07-30" @default.
• W4288826257 modified "2023-09-30" @default.
• W4288826257 title "Product allocation and network configuration in global production networks" @default.
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• W4288826257 doi "https://doi.org/10.1007/s11740-022-01149-4" @default.
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