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Location choice is a crucial planning task with major influence on a company’s future orientation and competitiveness. It is quite complex, since multiple location factors are usually of decision-relevance, incomparable, and sometimes conflictual. Further, ongoing urbanization is associated with locational dynamics posing major challenges for the regional location management of companies and municipalities. For example, respecting urban space as location factor, a scarcity growing over time leads to different assessment and requirements on a company’s behalf. For both companies and municipalities, there is a need for location development which implies an active change of location factor characteristics. Accordingly, considering locational dynamics is vital, as they may be decisive in the location decision-making. Although certain dynamics are considered within conventional Facility Location Problem (FLP) approaches, a systematic consideration of active location development is missing so far. Consequently, they may propagate long-term unfavorable location decisions, as major potentials associated with company-driven and municipal development measures are neglected. Therefore, this paper introduces a comprehensive decision support framework for the Regional Facility Location and Development planning Problem (RFLDP). It provides an operationalization of development measures, and thus anticipates dynamic adaptations to the environment. An established multi-criteria approach is extended to this new application. A complementary guideline ensures its meaningful applicability by practitioners. Based on a real-life case study, the decision support framework’s strength for practical application is demonstrated. Here, major advantages over conventional FLP approaches are highlighted. It is shown that the proposed methodology results in alternative location decisions which are structurally superior.

Due to the rapid growth of e-mobility, increasing amounts of lithium-ion batteries are produced and returned after their lifetime. However, these returns will lead to new challenges for manufacturers and recyclers, considering the end-of-life. Especially the increasing interaction between forward and reverse supply chain and the related decision on the end-of-life options (e.g., recycling, remanufacturing, and reuse) need to be planned and executed in a sophisticated way. Therefore, we focus on the interactions between recycler and manufacturer as two of the major actors of each supply chain. We formulate optimization models for the master recycling scheduling and the master production scheduling. To analyze current decentralized decisions of the recycler and remanufacturer, we further formulate an integrated master production and recycling scheduling model. In the following, we describe the production and recycling of lithium-ion batteries in a case study. Here, we examine five different scenarios. We find that for all scenarios, manufacturer and recycler achieve positive contribution margins. However, inefficiencies always occur due to opportunistic behavior. As a result, reuse is performed only in case of centralized planning. Hence, coordination is needed between the forward and reverse supply chain to achieve the maximal contribution margin.

The demand for electrical power in industrial production processes often leads to increasing energy costs for companies. In the course of a more sustainable power generation in the future, companies are faced with time-dependent energy prices, which have the potential to influence energy costs significantly. In order to manufacture the products at minimal decision-relevant total costs, planning approaches for production scheduling have to consider energy costs. To date, time-dependent energy prices are only considered in few production planning approaches in the field of job-shop scheduling and in some individual planning approaches in the field of simultaneous lot-sizing and scheduling. Up to now, a general model formulation for the consideration of time-dependent energy prices in lot-sizing and scheduling and an investigation of appropriate conditions for an energy-oriented production planning is missing. In this contribution, the energy-oriented general lot-sizing and scheduling problem is introduced as an extension of the respected general lot-sizing and scheduling problem. The cost saving potential is analyzed by considering energy in the lot-sizing and scheduling problem compared to classical planning approaches and appropriate frame conditions are investigated within a structured parameter analysis. In the numerical study, this leads to a total cost saving potential about 1.04% and an energy cost saving potential about 9.69%. In particular, a high volatility of the energy prices and a direct transfer of this volatility in form of short periods of constant energy prices increase this cost saving potential.

We consider multi-item single-source ordering with detailed consideration of transportation capacities. Such problems are characteristic for companies which operate direct links as part of their supply chain to transport loads with heterogeneous physical dimensions and fluctuating demands. Given knowledge on transportation demands, companies can eliminate future transports by shifting the load to fill the inflexible capacity of prior transports. While reducing transportation costs, doing so will ceteris paribus imply inventory. The problem is to coordinate orders across multiple items such that transport costs are minimized at minimal increase in inventory. The approach is distinct from prior works in that it considers detailed loading restrictions. We therefore interpret the problem as a multi-period version of the container loading problem. A wall building approach is used and incorporated into a heuristic rolling horizon procedure. We test the proposed procedure on some random problems which resemble a real inbound case from the automotive industry. As compared to period-by-period planning and two benchmarks with aggregated capacity models from the literature and practice, cost savings are possible under a wide range of operating conditions and mostly independent of the shipping volume. The largest potential exists for mid- to long-distance transports. There is a relevant potential to improve short-distance transports as well, however, only if inventory cost rates are moderate.

Over the past decades, robots have been heavily used for flow lines to increase productivity and product quality and to relieve workers of repetitive and dangerous tasks. However, despite continuous improvement of robots, the occurrence of failures remains a significant challenge in the operation of automated flow lines. Due to the connection of the stations in a flow line via a material handling system, failures at one station can quickly lead to throughput losses due to blocking and starving of upstream and downstream stations, respectively. To some extent, these throughput losses can be reduced by installing buffers between the stations. However, the installation of buffers requires considerable investments and scarce factory space. Therefore, the minimization of the total number of buffers is one of the primary objectives in flow line planning. Due to the advances of manufacturing technologies that form the foundation of “Industry 4.0”, new solutions to reduce throughput losses caused by equipment failures open up. One solution is a redundant configuration, in which downstream stations automatically take over the operations of failed stations in the event of failure. The throughput loss in these situations mainly depends on the level of redundancy designed into the system. Based on existing methods for the design of automated flow lines, we present two line balancing formulations for the configuration of automated flow lines under consideration of redundancies. The first formulation aims at maximizing the lines’ level of redundancy. The second formulation aims at a balanced allocation of redundancies along the line. To evaluate the presented formulations, we compare the performance with an existing line balancing approach for automated lines. With respect to this approach, improvements of the throughput rate between 3 % and 7 % are achieved.

Iron and steelmaking slags constitute important by-products of iron and steel production. Since slags are indispensable to iron and steel making processes, established recycling alternatives can be used to convert accruing slags to secondary resources, such as road construction materials, cements and fertilizers. The potential of a recycling alternative depends on a multitude of technical, economic and ecological influencing factors. In short-term production planning, the concurrence of these factors leads to the question how slags are to be recycled. The focus of this contribution is set on developing an adequate recycling planning approach based on techno-economic modelling. By combining activity analysis and flowsheet simulation, a modelling methodology is derived, which allows to model mechanical recycling processes characterized by particle size distributions. Further, management accounting and price functions are used to describe the occurring recycling costs and revenues for secondary resources, which are characterized by regional market structures. The developed concept is incorporated into a decision model, which is used in an illustrative example.

Currently, the German government strives for establishing Germany as a lead market for electric mobility. A successful growth of the electric vehicle market would be followed by a corresponding volume of spent lithium-ion batteries containing valuable and scarce metals. With their recycling, the high environmental load and energy use of primary production could be reduced, import dependencies could be diminished, and economic value could be created. Pioneering the mandatory deployment of an appropriate recycling network in Germany, the aim of this paper is to determine investment plans for the installation of recycling plants of different technologies and capacities and to derive recommendations for potential investors. For this purpose, a mathematical optimisation model is developed, allowing the economic selection of recycling technologies and capacities to be deployed in the network over time. In a comprehensive study, the impact of uncertain developments and mandatory minimum recycling rates on the timing of plant installations, on technology and capacity selection, on material flows, and on the profitability of recycling are analysed. The main finding is that despite the prevailing uncertainties a robust plan exists at least for initial decisions. It is shown that the recycling network can be operated highly economically in four out of five scenarios while meeting mandatory minimum recycling rates easily. By contrast, achieving both profitability and the minimum recycling rates will be a challenge if less valuable metals are used in the production of batteries, requiring the development of additional recycling steps to both reduce waste and increase profitability.

In distributed product development processes system integrators collaborate with suppliers to provide marketable products. We analyze contract structures in their ability to coordinate such processes. A converging supply chain with two suppliers and one system integrator is considered. Each supplier develops one component and faces uncertainty with regard to development results. For the system integrator the specifications of both components are substitutive in terms of the specification of the final product (e.g., recycling quotas). Depending on the resulting specification of the final product, the system integrator generates revenues under a maximum price clause. We apply a game-theoretic framework: the system integrator is the Stackelberg leader and the suppliers are Stackelberg followers. Assuming uniformly distributed development results, we analyze two typical development contracts: a wholesale price contract and a penalty contract. We present numerical illustrations of centralized and decentralized solutions to gain qualitative insights about the optimal decisions and the coordination ability of the two contracts. Accordingly, both contracts coordinate the supply chain only under forced compliance.

Bei der Unternehmensbewertung unter Unsicherheit ist nach unserer Auffassung die Unabhangigkeit der Bewertung von einer investorenseitigen sicheren Zahlung sowie von der Anzahl zu erwerbender Unternehmensanteile zu fordern. Diese Forderungen entsprechen formal einem linearen Bewertungsfunktional, also Wertadditivitat im Hinblick auf additive und (positive) multiplikative Konstante.