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.
We study a workforce planning and scheduling problem in which weekly tours of agents must be designed. Our motivation for this study comes from a call center application where agents serve customers in response to inc...
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We study a workforce planning and scheduling problem in which weekly tours of agents must be designed. Our motivation for this study comes from a call center application where agents serve customers in response to incoming phone calls. Similar to many other applications in the services industry, the demand for service in call centers varies significantly within a day and among days of the week. In our model, a weekly tour of an agent consists of five daily shifts and two days off, where daily shifts within a tour may be different from each other. The starting times of any two consecutive shifts, however, may not differ by more than a specified bound. Furthermore, a tour must also satisfy constraints regarding the days off, for example, it may be required that one of the days off is on a weekend day. The objective is to determine a collection of weekly tours that satisfy the demand for agents' services, while minimizing the total labor cost of the workforce. We describe an integer programming model where a weekly tour is obtained by combining seven daily shift scheduling models and days-off constraints in a network flow framework. The model is flexible and can accommodate different daily models with varying levels of detail. It readily handles different days-off rules and constraints regarding start time differentials in consecutive days. Computational results are also presented. (C) 2001 John Wiley & Sons, Inc.
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.
Order Review and Release (ORR) is a comprehensive approach to job-shop scheduling. Load-Oriented Manufacturing Control (LOMC) is an effective ORR method, and it restricts the workload of workstations by periodically r...
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ISBN:
(纸本)9781424448692
Order Review and Release (ORR) is a comprehensive approach to job-shop scheduling. Load-Oriented Manufacturing Control (LOMC) is an effective ORR method, and it restricts the workload of workstations by periodically release right orders into workshop. When selecting orders, "balancing workload" and "meeting order due date" are two contradict objectives. LOMC puts more emphasis on the latter. However, previous studies show that "balancing workload" is quite important, and priority should be given to "balancing workload" when order due dates show small difference. So it improves the order release procedure of LOMC by applying a 0-1 integer programming model to coordinate the two objectives delicately. The new method is named ILOMC (integer-programming-model-based LOMC). Simulation experiments have been carried out to compare LOMC and ILOMC. Simulation results show that ILOMC outperforms LOMC as it can better balance workload.
In this paper, we present a two-stage solution approach to a special VRP, which can be described as follows: all customers scattering around the depot are divided into a number of circular area;they must be satisfied ...
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ISBN:
(纸本)9789806560710
In this paper, we present a two-stage solution approach to a special VRP, which can be described as follows: all customers scattering around the depot are divided into a number of circular area;they must be satisfied within a specified time window;several kinds of vehicles are used. The objective of the first stage is to generate possible delivery schemes for each type of vehicles, in which depth-first search strategy of the state-space theory in Artificial Intelligence (AI) is used. It is remarkable that a vehicle's travel time constraint and load capacity constraint are used to control the search depth in this stage. Simultaneously, two strategies are introduced to decrease the number of feasible schemes by eliminating some worse schemes. In the second stage, an integer programming model is constructed to work out the optimal routing schemes from the first stage's outcome. Based on the proposed two-stage approach, a solving system is developed to solve the above mentioned kind of VRP. Also a real VRP case, which contains 106 customers and two kinds of vehicles, is studied to test the effectiveness and efficiency of the approach. The study creates a new way of solving this kind of NP-hard problems.
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 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.
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.
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