scholarly journals Optimal model for the aircraft arrival and departure scheduling problem with fuzzy runway incursion time

2021 ◽  
Vol 18 (5) ◽  
pp. 6724-6738
Author(s):  
Bo Sun ◽  
◽  
Ming Wei ◽  
Binbin Jing ◽  
◽  
...  
Keyword(s):  
Real World ◽  
Queuing Theory ◽  
Polynomial Algorithm ◽  
Scheduling Problem ◽  
Optimal Model ◽  
Flight Delays ◽  
Scheduling Scheme ◽  
Air Traffic Controllers ◽  
Queue Lengths ◽  
Runway Incursion

<abstract> <p>This paper presents an optimization model for assigning a set of arrival and departure flights to multiple runways and determining their actual times with consideration of incursions. Due to the lack of data, fuzzy incursion time is used to describe the uncertainty with the help of artificial experience. Moreover, the multiple-goal priority considerations of air traffic controllers are also fully considered in this model. The two objectives are to simultaneously minimize delays in arrival and departure flights. Since this problem is NP-hard, a novel polynomial algorithm based on queuing theory is also proposed to obtain acceptable solutions efficiently. Finally, a real-world example is provided to analyze the effect of different times and places of incursion events on the scheduling scheme, which can verify the correctness of the model. Results show that higher runway incursion times lead to longer queue lengths for take-off and landing flights, resulting in more flight delays.</p> </abstract>

A multi-shop integrated scheduling algorithm with fixed output constraint

2021 ◽  
pp. 1-9
Author(s):  
Yingchun Xia ◽  
Zhiqiang Xie ◽  
Yu Xin ◽  
Xiaowei Zhang
Keyword(s):  
Constraint Programming ◽  
Programming Model ◽  
Scheduling Algorithm ◽  
Processing Parameters ◽  
Scheduling Problem ◽  
Integrated Scheduling ◽  
Scheduling Scheme ◽  
Wide Range ◽  
Constraint Programming Model ◽  
Output Constraint

The customized products such as electromechanical prototype products are a type of product with research and trial manufacturing characteristics. The BOM structures and processing parameters of the products vary greatly, making it difficult for a single shop to meet such a wide range of processing parameters. For the dynamic and fuzzy manufacturing characteristics of the products, not only the coordinated transport time of multiple shops but also the fact that the product has a designated output shop should be considered. In order to solve such Multi-shop Integrated Scheduling Problem with Fixed Output Constraint (MISP-FOC), a constraint programming model is developed to minimize the total tardiness, and then a Multi-shop Integrated Scheduling Algorithm (MISA) based on EGA (Enhanced Genetic Algorithm) and B&B (Branch and Bound) is proposed. MISA is a hybrid optimization method and consists of four parts. Firstly, to deal with the dynamic and fuzzy manufacturing characteristics, the dynamic production process is transformed into a series of time-continuous static scheduling problem according to the proposed dynamic rescheduling mechanism. Secondly, the pre-scheduling scheme is generated by the EGA at each event moment. Thirdly, the jobs in the pre-scheduling scheme are divided into three parts, namely, dispatched jobs, jobs to be dispatched, and jobs available for rescheduling, and at last, the B&B method is used to optimize the jobs available for rescheduling by utilizing the period when the dispatched jobs are in execution. Google OR-Tools is used to verify the proposed constraint programming model, and the experiment results show that the proposed algorithm is effective and feasible.

scholarly journals A Two-Stage Offline-to-Online Multiobjective Optimization Strategy for Ship Integrated Energy System Economical/ Environmental Scheduling Problem

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Qing An ◽  
Jun Zhang ◽  
Xin Li ◽  
Xiaobing Mao ◽  
Yulong Feng ◽  
...  
Keyword(s):  
Multiobjective Optimization ◽  
Real World ◽  
Operation Time ◽  
Energy System ◽  
Scheduling Problem ◽  
Storage Space ◽  
Optimization Strategy ◽  
Two Stage ◽  
Integrated Energy System ◽  
And Storage

The economical/environmental scheduling problem (EESP) of the ship integrated energy system (SIES) has high computational complexity, which includes more than one optimization objective, various types of constraints, and frequently fluctuated load demand. Therefore, the intelligent scheduling strategies cannot be applied to the ship energy management system (SEMS) online, which has limited computing power and storage space. Aiming at realizing green computing on SEMS, in this paper a typical SIES-EESP optimization model is built, considering the form of decision vectors, the economical/environmental optimization objectives, and various types of real-world constraints of the SIES. Based on the complexity of SIES-EESPs, a two-stage offline-to-online multiobjective optimization strategy for SIES-EESP is proposed, which transfers part of the energy dispatch online computing task to the offline high-performance computer systems. The specific constraints handling methods are designed to reduce both continuous and discrete constraints violations of SIES-EESPs. Then, an establishment method of energy scheduling scheme-base is proposed. By using the big data offline, the economical/environmental scheduling solutions of a typical year can be obtained and stored with more computing resources and operation time on land. Thereafter, a short-term multiobjective offline-to-online optimization approach by SEMS is considered, with the application of multiobjective evolutionary algorithm (MOEA) and typical schemes corresponding to the actual SIES-EESPs. Simulation results show that the proposed strategy can obtain enough feasible Pareto solutions in a shorter time and get well-distributed Pareto sets with better convergence performance, which can well adapt to the features of real-world SIES-EESPs and save plenty of operation time and storage space for the SEMS.

scholarly journals Mathematical models for a batch scheduling problem to minimize earliness and tardiness

2018 ◽  
Vol 11 (3) ◽  
pp. 390 ◽  
Author(s):  
Basar Ogun ◽  
Çigdem Alabas-Uslu
Keyword(s):  
Mathematical Models ◽  
Real World ◽  
Lean Manufacturing ◽  
Programming Model ◽  
Computational Study ◽  
Batch Scheduling ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Earliness And Tardiness ◽  
Customer Orders

Purpose: Today’s manufacturing facilities are challenged by highly customized products and just in time manufacturing and delivery of these products. In this study, a batch scheduling problem is addressed to provide on-time completion of customer orders in the environment of lean manufacturing. The problem is to optimize partitioning of product components into batches and scheduling of the resulting batches where each customer order is received as a set of products made of various components.Design/methodology/approach: Three different mathematical models for minimization of total earliness and tardiness of customer orders are developed to provide on-time completion of customer orders and also, to avoid from inventory of final products. The first model is a non-linear integer programming model while the second is a linearized version of the first. Finally, to solve larger sized instances of the problem, an alternative linear integer model is presented.Findings: Computational study using a suit set of test instances showed that the alternative linear integer model is able to solve all test instances in varying sizes within quite shorter computer times comparing to the other two models. It was also showed that the alternative model can solve moderate sized real-world problems.Originality/value: The problem under study differentiates from existing batch scheduling problems in the literature since it includes new circumstances which may arise in real-world applications. This research, also, contributes the literature of batch scheduling problem by presenting new optimization models.

Using Optimization Techniques and Multidisciplinary Collaboration to Solve a Challenging Real-World Residency Scheduling Problem

2019 ◽  
Vol 49 (3) ◽  
pp. 201-212
Author(s):  
Young-Chae Hong ◽  
Amy Cohn ◽  
Stephen Gorga ◽  
Edmond O’Brien ◽  
William Pozehl ◽  
...  
Keyword(s):  
Real World ◽  
Optimization Techniques ◽  
Scheduling Problem ◽  
Multidisciplinary Collaboration

Flight Flow Balanced Allocation in Terminal Airspace

2013 ◽  
Vol 441 ◽  
pp. 602-606
Author(s):  
Wei Jun Pan ◽  
Wen Bin Qiu ◽  
Rui Kang
Keyword(s):  
Integer Programming ◽  
Programming Model ◽  
Air Traffic ◽  
Nonlinear Integer Programming ◽  
Flight Delays ◽  
Air Traffic Controllers ◽  
Balanced Allocation ◽  
Airport Terminal ◽  
Flight Route ◽  
Better Than

A nonlinear integer programming model (NIPM) with constraints is proposed to solve the allocation of approach flight flow where ends with terminal airspace, an example of an airport terminal airspace is given, where the flow is accurately forecasted.Analysising flight delays, theres a conclusion: the results solved by NIPM is far better than the average allocation method, for the second-level airspace, NIPM can reduce two flight delays, and the allocation in each flight route tends to be equilibrium, NIPM can also provide air traffic controllers with accurate and reasonable allocation schedule.

Research on Multitask Collaborative Scheduling Problem with Heuristic Strategies

2011 ◽  
Vol 66-68 ◽  
pp. 758-763
Author(s):  
Fan Zhang ◽  
Gui Fa Teng ◽  
Jian Bin Ma ◽  
Jie Yao
Keyword(s):  
Scheduling Algorithm ◽  
Scheduling Problem ◽  
Agricultural Machinery ◽  
Start Time ◽  
Farm Machinery ◽  
Scheduling Scheme ◽  
Scheduling Model ◽  
Heuristic Strategies ◽  
Collaborative Scheduling ◽  
Minimal Resource

According to problems existed in the current farm machinery scheduling process, a new farm machinery scheduling scheme is adopted in this dissertation. The collaborative scheduling model of farm machinery is established and multitask collaborative scheduling algorithm is designed through analyzing the differences between Vehicle Scheduling Problem and agricultural machinery scheduling in the dissertation. Earliest Start Time First and minimal resource allocated capacity first strategies are used in the farm machinery scheduling. The algorithm is useful for the case of machinery owner with sufficient farm machinery. The experiment proves that the collaborative scheduling algorithm is more effective than the serial scheduling algorithm.

scholarly journals A Simheuristic Method for the Reversible Lanes Allocation and Scheduling Problem at Smart Container Terminal Gate

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Wenyuan Wang ◽  
Ying Jiang ◽  
Yun Peng ◽  
Yong Zhou ◽  
Qi Tian
Keyword(s):  
Theoretical Foundation ◽  
Container Terminal ◽  
Service Level ◽  
Scheduling Problem ◽  
Metaheuristic Algorithm ◽  
Optimal Model ◽  
Practice Parameters ◽  
Traffic Volumes ◽  
Gate System ◽  
Northeast Of China

Under the constraints of limited spaces and imbalanced traffic volumes (for both in and out directions) of container gates, reversible lane layouts become an economical and practical way to improve the service level of container terminal systems and make the maximum use of the current terminal resources. Together with a consideration of minimized total costs (both construction and operating) of terminal gate system, this paper first developed an optimization model to decide the number and scheduling rules of the reversible lanes at a terminal gate. A metaheuristic algorithm was built to solve the optimal model. Meanwhile, to reflect the randomness and dynamics property of the terminal gate system in practice, parameters that cannot be calculated from conventional analytic methods are obtained through a simulation model. Finally, a hub container terminal in the northeast of China was employed to verify the effectiveness of the proposed method and provide a theoretical foundation for the construction and management of terminal gate systems.

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