Central European Journal of Operations Research最新文献

This paper addresses the optimization of resource allocation and infrastructure planning in bike-sharing systems, particularly inspired by dynamic demand patterns as observed during the COVID-19 pandemic. We introduce a stochastic mathematical model that considers varying demand scenarios to enhance system performance and resource utilization. The research objectives are to fulfill the total travel demand across scenarios and compute the network's capacity to satisfy demand, thereby enhancing the system's efficiency and meeting users' diverse travel needs. The main contributions of this paper include presenting a stochastic mathematical model for bike-sharing station allocation and path network design, which optimizes resource allocation and infrastructure planning. Through a case study on the Vienna bike-sharing system, the model demonstrates practical applicability and effectiveness, offering insights for improving efficiency and service quality. The sensitivity analysis reveals that as costs for bicycle docks and station building increase, fulfilled demand decreases, emphasizing the crucial role of cost management in meeting demand efficiently.

We examine some of the opportunities and challenges concerned with establishing a centralized national kidney exchange program in Germany. Despite the many advantages of a national program, without deliberate design and policy intervention, a fragmented kidney exchange program may emerge. We study a number of collaboration strategies, and resulting simulations suggest that transplant centers may find it advantageous not to fully participate, resulting in a net reduction in the number of transplants. These results also suggest that allowing more forms of kidney exchange, such as three-way exchanges and non-directed donations, can significantly increase the number of transplants while making participation in a national program more attractive and thus national coordination and cooperation more robust. We propose a multi-level policy approach that is easy to implement and would promote an efficient German kidney exchange program that benefits recipients, donors and hospitals.

In this paper, we modify and extend a model of macroeconomic stabilization policies for a dynamic economy by Leitmann and Wan. We combine a model of long-run output growth and a steady state of no growth with a model of short-run deviations from this growth path based on Keynesian and Monetarist macroeconomic hypotheses. We determine numerically the effects of demand and supply shocks and approximately optimal reactions of fiscal and monetary policies to these shocks for a policy maker in charge of both fiscal and monetary policy using an optimal control algorithm. We also formulate a dynamic game between government (fiscal policy) and central bank (monetary policy) with separate instruments and different preferences for the trade-off between unemployment and inflation and solve it numerically for the noncooperative feedback Nash equilibrium solution and a Pareto optimal solution. The results provide insights into the possibilities of active fiscal and monetary policies and of cooperation and possible conflicts between the institutions responsible for these policies.

The management of truck arrivals at container terminals is crucial for efficient port operations. Congestions developing both outside and inside the gates can cause logistical problems, while also having a significant impact on the environment and the surroundings of the port. Therefore, optimizing truck queues outside the gates of the port, as well as routing of trucks inside the terminals can lead to an improvement in the overall efficiency of the port processes. This paper presents a mixed-integer linear programming formulation to determine these optimal truck routes and schedules. The model considers a port with an external parking lot, multiple gates, internal roadways, and docks. A rolling horizon heuristic is also developed for the solution of instances where the model is otherwise intractable. The developed methods are evaluated on instances simulated based on real-world data.

Combinatorial auctions are an important part of many frameworks for carrier collaboration in logistics. In the last years, many innovative auction mechanisms have been developed in the economic literature that could potentially be applied in this context and that could significantly simplify the process of determining efficient allocations of requests. These mechanisms rely on certain assumptions about the valuations of bidders. In this paper, we perform computational experiments to analyze to which extent these requirements are fulfilled for valuations derived from a simple logistics problem, the Traveling Salesman Problem. We find that bidders' valuations typically violate even very elementary requirements, but that these violations affect only a limited number of request bundles. We further analyze whether these violations exhibit a consistent pattern across multiple carriers and check consistency if route lengths are calculated exactly or approximated.

Supplementary information: The online version contains supplementary material available at 10.1007/s10100-023-00873-1.