The steel plate yard of shipbuilding separates the inbound and pre-processing operations, increasing the number of moves. This paper considers the mixed inbound and pre-processing operation and studies the stack inbou...
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The steel plate yard of shipbuilding separates the inbound and pre-processing operations, increasing the number of moves. This paper considers the mixed inbound and pre-processing operation and studies the stack inbound and pre-marshalling problem where storage and relocation moves can alternate. This problem aims to find a minimum operation to store all inbound plates while eliminating all blocking plates. We propose a novel integer programming model combining two moves in one time period. This model reduces the number of periods, thereby decreasing the model size, but requires extra constraints to avoid infeasible patterns. An exact branch-and-cut algorithm is introduced to tackle the influence of these extra constraints. This paper provides a new modeling approach for stack-related problems, and the experiments show that the proposed method outperforms other ILP-based methods in the literature.
The shared self-service check-in system can effectively alleviate the tension of airport caused by limited resources in the future. The effective allocation of resources is the key to improving the performance of this...
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The shared self-service check-in system can effectively alleviate the tension of airport caused by limited resources in the future. The effective allocation of resources is the key to improving the performance of this collaborative work system. In this paper, an associative decision integer programming model is established to quantitatively describe the total baggage handling time of the collaborative work system by using piece-wise functions under different allocation schemes. In order to meet passengers' expectation of queuing time, the queue system is optimized to constrain the service level, and eventually the system efficiency is significantly improved. The discrete event simulation results show that the allocation scheme generated by the model can not only largely improve the equipment utilization rate by 124%, but is also able to shorten the queuing time of passengers by 72.8%, which provides the possibility to comprehensively optimize and improve the efficiency of future airport baggage handling systems.
In this work, we consider the Vehicle Routing Problem with Simultaneous Delivery and Pickup, and constrained by time windows, to improve the performance and responsiveness of the supply chain by transporting goods fro...
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In this work, we consider the Vehicle Routing Problem with Simultaneous Delivery and Pickup, and constrained by time windows, to improve the performance and responsiveness of the supply chain by transporting goods from one location to another location in an efficient manner. In this class of problem, each customer demands a quantity to be delivered as a part of the forward supply service and another quantity to be picked up as a part of the reverse recycling service, and the complete service has to be done simultaneously in a single visit of a vehicle, and the objective is to minimize the total cost, which includes the traveling cost and dispatching cost for operating vehicles. We propose a Mixed integer Linear programming (MILP) model for solving this class of problem. In order to evaluate the performance of the proposed MILP model, a comparison study is made between the proposed MILP model and an existing MILP model available in the literature, with the consideration of heterogeneous vehicles. Our study indicates that the proposed MILP model gives tighter lower bound and also performs better in terms of the execution time to solve each of the randomly generated problem instances, in comparison with the existing MILP model. In addition, we also compare the proposed MILP model (assuming homogeneous vehicles) with the existing MILP model that also considers homogeneous vehicles. The results of the computational evaluation indicate that the proposed MILP model gives much tighter lower bound, and it is competitive to the existing MILP model in terms of the execution time to solve each of the randomly generated problem instances.
The shift scheduling, which is one of the most crucial processes in order to increase efficiency and decrease labor costs, is a common phenomenon in both manufacturing and service organizations such as airlines, secur...
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The shift scheduling, which is one of the most crucial processes in order to increase efficiency and decrease labor costs, is a common phenomenon in both manufacturing and service organizations such as airlines, security services, fire stations, etc. In order to meet changing demand and keep responsiveness and flexibility, the shift scheduling includes the scheduling of manpower by assigning employees to shifts determined by types, length, and the number of breaks. The types of shifts may present variety such as part time and full time shifts. The breaks also show variety like lunch breaks, short rests, and compulsory reasons based on the occupational health and safety or necessities for maintenance. To overwhelm this complexity, this paper recommends an integer programming model integrated with fuzzy logic due to the vagueness inherited to the nature of decision-making process in order to provide flexibility in shift lengths, and lower the total labor costs.
In the context of limited airport capacity, the increasing imbalance between growing air traffic demand and constrained airport capacity significantly elevates the probability of flight delays or even cancellations. T...
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In the context of limited airport capacity, the increasing imbalance between growing air traffic demand and constrained airport capacity significantly elevates the probability of flight delays or even cancellations. To address this issue, this paper proposes a strategic flight planning model based on integerprogramming from the perspective of airport capacity. The model incorporates constraints such as departure, arrival, and total capacity, aiming to adjust flight schedules at the strategic phase to more effectively utilize existing airport *** the example of adjusting flight schedules from Chengdu Shuangliu International Airport, direct to Tengchong Tuofeng Airport, to Chengdu Shuangliu International Airport first and then to Dehong Mangshi International Airport, the paper demonstrates, through strategic flight planning, a more balanced alignment of flight demand and airport capacity without increasing the burden on the airport. This validates the practicality and effectiveness of the proposed model. The research results indicate that the model can effectively improve abnormal flight situations while reducing operational costs, providing significant convenience for airports, airlines, and passengers.
Considering the reduction of aerodynamic drag of the virtually linked truck's slipstream in a trainlike convoy has brought benefits such as significant fuel consumption savings, truck platooning has been identifie...
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Considering the reduction of aerodynamic drag of the virtually linked truck's slipstream in a trainlike convoy has brought benefits such as significant fuel consumption savings, truck platooning has been identified as a promising operational technology. To fully reap these benefits in the initial phases of truck platooning deployment, an appropriate truck platooning plan based on itineraries and deadlines of each transportation task is required. We construct a truck platooning routing and scheduling optimization model with minimum overall system fuel consumption considering detour costs and time restrictions. Meanwhile, we introduce the linearizing method and give recommendations on the values for Big-${\rm M}$M to ensure the efficient solution of the optimization model. To demonstrate the effectiveness and efficiency of the proposed model, various randomly generated road networks are constructed and the truck platooning routing and scheduling optimization model is solved. The model provides valuable insights regarding platooning plan from a transportation optimization and scheduling perspective.
BackgroundBreast and cervical cancers are the commonest cancers among women. Secondary prevention of cancer through screening minimizes disease burden and improves survival outcomes. Optimizing screening strategies fo...
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BackgroundBreast and cervical cancers are the commonest cancers among women. Secondary prevention of cancer through screening minimizes disease burden and improves survival outcomes. Optimizing screening strategies for breast and cervical cancers is a challenge in resource-limited settings with a high population density such as China. Therefore, we aimed at assessing the efficiency of different combined screening strategies for breast and cervical cancers under different budgets in *** cohort model was used to evaluate the cost-effectiveness of 36 strategy combinations for breast and cervical cancer screening with varying screening modality and intervals. The results were used as inputs in the integerprogramming (IP) model to determine the combination of the different screening options under different *** optimal combination strategy was biennial breast ultrasonography (BUS) and mammography (MAM) in parallel screening and quinquennial human papillomavirus (HPV) for breast and cervical cancer screening under the threshold of the annual per capita social cost investment (PCSCI) (18.80 USD) in China. Using this strategy, the total investment cost for 100,000 females was 1,877,984.50 USD, and the incremental life-years compared with no screening was 3,122 life-years. The optimal combination strategy included annual clinical breast examination (CBE), BUS and MAM in series screening, and biennial thin-layer liquid-based cytology (TCT) and HPV in series screening with the annual PCSCI reaching 37.60 USD. Thereafter, as the cost input continued to increase, the optimal combination strategy remained unchanged, and the sum of incremental life-years and actual input costs did not *** a social cost-benefit perspective, biennial BUS and MAM in parallel screening, and quinquennial HPV screening is the most efficient combination strategy with limited budget, while annual CBE, BUS and MAM in series screening and biennial TCT and
Considering the unique interplay of trams with road traffic, this study explored the issue of instability in tram operations-a prominent medium-capacity rail transit. Our goal was to design a timetable slack time opti...
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Considering the unique interplay of trams with road traffic, this study explored the issue of instability in tram operations-a prominent medium-capacity rail transit. Our goal was to design a timetable slack time optimization method for scheduling slack time to improve the stability of tram operations. To facilitate this, we derived the travel/dwelling time distribution from historical data, which assisted in estimating interference times and evaluating the requisite slack time. We then developed an integer programming model to calculate both the punctuality rate and expected delay under varying travel times, enabling the creation of alternative slack time schemes. Using a unique tram operation simulation logic, we assessed the operational efficiency and reliability of these alternate schemes based on specific operational indicators. The results suggest that our novel approach to timetable optimization significantly enhances the tram's adaptability to disruptions, directly improving the passenger experience and tram competitiveness. This work offers a robust framework for timetable optimization for semi-independent right-of-way public transportation.
To improve passenger accessibility and reduce the travel time cost at night, this paper aims to optimize the synchronization of the last several trains' timetables on each line of an urban rail transit (URT) net-w...
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To improve passenger accessibility and reduce the travel time cost at night, this paper aims to optimize the synchronization of the last several trains' timetables on each line of an urban rail transit (URT) net-work. A space-time network is constructed to describe the train flow and passenger flow in the URT network, based on which an integer programming model is formulated. To effectively solve the proposed model, we decompose the problem into two levels and propose an iterative algorithm. In the upper level, an adaptive large neighbourhood search (ALNS) method is developed to generate new train timetables in the URT network, which are then evaluated by the passenger flow problem in the lower level, and the optimization-evaluation iteration continues until the termination conditions are met. The method and algorithm are applied to a large-scale instance using data for the Wuhan URT network at night, which involve 9 urban rail transit lines and over 119,0 0 0 passengers, and the results show that the number of inaccessible passengers is reduced by 27 . 53% , and the average travel time cost is reduced by 2 . 70% , com-pared with the original timetable. Then, the experimental results on a small-scale instance show that the proposed algorithm can find a near-optimal solution in a short time, which illustrates the effectiveness and efficiency of the ALNS method.(c) 2023 Elsevier B.V. All rights reserved.
Supplier selection and order allocation are major tasks to companies in green supply chain management. Most literatures consider these two tasks as independent sub-problems. In this paper, we propose an integrated two...
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Supplier selection and order allocation are major tasks to companies in green supply chain management. Most literatures consider these two tasks as independent sub-problems. In this paper, we propose an integrated two-stage multiple criteria programming approach to solve them systematically. The approach includes both quantitative and qualitative analyses. In the first stage, an MULTIMOORA method based on linguistic Z-Numbers is employed to rank the green suppliers under multiple qualitative criteria (but that is not the final decision). In the second stage, the ranking result is input to a bi-objective non-linear integer programming model. The model then determines the suppliers selected and the quantity of order allocated to them. Furthermore, the model should determine the configuration of the productions because different configuration implies different resource needed. We present the comparative result with other quantitative methods. An illustrative example proves that our proposed model can achieve the desired consistency among objectives.
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