Given the growing demand for tourism and an aging population, the need for escort services in airport operations is increasing steadily. Therefore, optimizing the dispatching of escorts to reduce waiting times for pas...
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Given the growing demand for tourism and an aging population, the need for escort services in airport operations is increasing steadily. Therefore, optimizing the dispatching of escorts to reduce waiting times for passengers with reduced mobility is currently a significant concern. This study utilizes the time-space network technique and mathematical programming to develop a model for escort manpower supply planning and scheduling, aiming to minimize manpower needs. Additionally, the model incorporates service delay and task aborting strategies to better reflect real-world scenarios. To efficiently solve the model, we introduce both a relax-and-fix algorithm and a fairness-considerate flow decomposition algorithm. Using data from a Taiwan international airport, we conduct a case study and perform sensitivity/scenario analysis on various parameters. The results highlight the potential of the developed model and algorithms in effectively managing manpower supply planning, escort dispatching, and task assignment in practical situations.
In this paper, we consider a lot-sizing and scheduling problem arising in the real-world flat-panel display industry. This problem is formulated as a variant of the discrete lot-sizing and scheduling problem with a se...
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In this paper, we consider a lot-sizing and scheduling problem arising in the real-world flat-panel display industry. This problem is formulated as a variant of the discrete lot-sizing and scheduling problem with a sequence-dependent setup. After describing the characteristics of the problem and analyzing its computational complexity, we propose an extended formulation based on a network structure. Even though the problem is NP-hard in general, we show that there exist special cases solvable in polynomial time. For the general cases, we demonstrate the tightness of the extended formulation by means of both polyhedral analysis and computational experiments with artificially generated data and real-world industry data. We also propose a relax-and-fix heuristic algorithm based on the extended formulation, which has been deployed in practice, with the corresponding computational results. (C) 2019 Elsevier Ltd. All rights reserved.
In this paper, we study the hierarchical hub network design problem with a ring-star-star structure. In this problem, the hubs are located in two layers. In the first layer, central hubs (main hubs) are located in a r...
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In this paper, we study the hierarchical hub network design problem with a ring-star-star structure. In this problem, the hubs are located in two layers. In the first layer, central hubs (main hubs) are located in a ring structure, and in the second layer, secondary hubs are located. Each secondary hub is allocated to a central hub. Other demand points can also be allocated to each of these hubs (central hubs or secondary hubs). The objective is to minimize transportation costs on the network. This problem applies to communication networks when establishing direct links between demand nodes is not cost-effective, and there are two levels of service for customers. Also, the ring structure is used to reduce costs associated with full communication between central hubs. We present a mixed-integer programming model for the problem and report the results of the problem solving for a numerical example on the CAB dataset. Also, we present three solution methods for the problem. First, by exploiting the decomposable structure of the proposed model, we introduce an accelerated Benders decomposition algorithm. Then, we present a hybrid genetic algorithm that uses the Dijkstra algorithm to evaluate solutions. Next, we present a hybrid variable neighborhood search algorithm that uses the Dijkstra algorithm to calculate the cost of each solution. Also, a relax-and-fix algorithm is proposed to find near-optimal feasible solutions for the problem. Computational results are presented on the USA423 dataset. The results show that the proposed relax-and-fix algorithm can solve instances with up to 100 nodes. Also, the proposed hybrid algorithms can solve instances with up to 423 nodes. The performance of the proposed hybrid variable neigh-borhood search is better than the proposed hybrid genetic algorithm in solving large-sized instances.
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