Hybrid of Hill Climbing and SAT Solving for Air Traffic Controller Shift Scheduling

Modern computers solve many problems by using exact methods, heuristic methods and very often by using their combination. Air Traffic Controller Shift Scheduling Problem has been successfully solved by using SAT technology (reduction to logical formulas) and several models of the problem exist. We present a technique for solving this problem that is a combination of SAT solving and meta-heuristic method hill climbing, and consists of three phases. First, SAT solver is used to generate feasible solution. Then, the hill climbing is used to improve this solution, in terms of number of satisfied wishes of controllers. Finally, SAT solving is used to further improve the found solution by fixing some parts of the solution. Three phases are repeated until optimal solution is found. Usage of exact method (SAT solving) guarantees that the found solution is optimal; usage of meta-heuristic (hill climbing) increases the efficiency in finding good solutions. By using these essentially different ways of solving, we aim to use the best from both worlds. Results indicate that this hybrid technique outperforms previously most efficient developed techniques.

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Solving methods for the quay crane scheduling problem at port of Tripoli-Lebanon.

RAIRO - Operations Research ◽

10.1051/ro/2020135 ◽

2020 ◽

Author(s):

Ali Skaf ◽

Sid Lamrous ◽

Zakaria Hammoudan ◽

Marie-Ange Manier

Keyword(s):

Dynamic Programming Algorithm ◽

Heuristic Method ◽

Optimal Solution ◽

Mixed Integer ◽

Programming Algorithm ◽

Scheduling Problem ◽

Exact Methods ◽

Three Solutions ◽

Quay Crane Scheduling ◽

Crane Scheduling

The quay crane scheduling problem (QCSP) is a global problem and all ports around the world seek to solve it, to get an acceptable time of unloading containers from the vessels or loading containers to the vessels and therefore reducing the docking time in the terminal. This paper proposes three solutions for the QCSP in port of Tripoli-Lebanon, two exact methods which are the mixed integer linear programming and the dynamic programming algorithm, to obtain the optimal solution and one heuristic method which is the genetic algorithm, to obtain near optimal solution within an acceptable CPU time. The main objective of these methods is to minimize the unloading or the loading time of the containers and therefore reduce the waiting time of the vessels in the terminals. We tested and validated our methods for small and large random instances. Finally, we compared the results obtained with these methods for some real instances in the port of Tripoli-Lebanon.

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Air Traffic Controller Shift Scheduling by Reduction to CSP, SAT and SAT-Related Problems

Lecture Notes in Computer Science - Principles and Practice of Constraint Programming ◽

10.1007/978-3-319-10428-7_63 ◽

2014 ◽

pp. 886-902 ◽

Cited By ~ 1

Author(s):

Mirko Stojadinović

Keyword(s):

Air Traffic ◽

Shift Scheduling ◽

Air Traffic Controller

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The Air Traffic Controller Work-Shift Scheduling Problem in Spain from a Multiobjective Perspective: A Metaheuristic and Regular Expression-Based Approach

Mathematical Problems in Engineering ◽

10.1155/2018/4719178 ◽

2018 ◽

Vol 2018 ◽

pp. 1-15 ◽

Cited By ~ 1

Author(s):

Faustino Tello ◽

Alfonso Mateos ◽

Antonio Jiménez-Martín ◽

Adán Suárez

Keyword(s):

Simulated Annealing ◽

Rank Order ◽

Optimal Solution ◽

Air Traffic ◽

Second Phase ◽

Scheduling Problem ◽

Shift Scheduling ◽

Work Shift ◽

Labor Conditions ◽

Feasible Solutions

We address an air traffic control operator (ATCo) work-shift scheduling problem. We consider a multiple objective perspective where the number of ATCos is fixed in advance and a set of ATCo labor conditions have to be satisfied. The objectives deal with the ATCo work and rest periods and positions, the structure of the solution, the number of control center changes, or the distribution of the ATCo workloads. We propose a three-phase problem-solving methodology. In the first phase, a heuristic is used to derive infeasible initial solutions on the basis of templates. Then, a multiple independent run of the simulated annealing metaheuristic is conducted aimed at reaching feasible solutions in the second phase. Finally, a multiple independent simulated annealing run is again conducted from the initial feasible solutions to optimize the objective functions. To do this, we transform the multiple to single optimization problem by using the rank-order centroid function. In the search processes in phases 2 and 3, we use regular expressions to check the ATCo labor conditions in the visited solutions. This provides high testing speed. The proposed approach is illustrated using a real example, and the optimal solution which is reached outperforms an existing template-based reference solution.

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A heuristic method for solving airline crew pairing problems

MATEC Web of Conferences ◽

10.1051/matecconf/201820402006 ◽

2018 ◽

Vol 204 ◽

pp. 02006

Author(s):

Khusnul Novianingsih ◽

Rieske Hadianti

Keyword(s):

Optimization Problems ◽

Heuristic Method ◽

Optimal Solution ◽

Exact Methods ◽

Flight Schedules ◽

Airline Crew ◽

Short Period ◽

Crew Pairing ◽

Local Optimal Solution ◽

Airline Schedules

The airline crew pairing problem is one of the optimization problems which classified as a NP-hard problem. Since the number of feasible pairings in flight schedules can be numerous, the exact methods will not efficient to solve the problem. We propose a heuristic method for solving crew pairing problems. Initially, we generate a feasible solution by maximizing the covered flights. Then, we improve the solution by constructing a procedure to avoid the local optimal solution. We test our method to an airline schedules. The computational results show that our method can give the optimal solution in short period of time.

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Predictive Validity of a Selection Procedure for Air Traffic Controller Trainees

Aviation Psychology and Applied Human Factors ◽

10.1027/2192-0923/a000039 ◽

2013 ◽

Vol 3 (1) ◽

pp. 19-27 ◽

Cited By ~ 6

Author(s):

Yvonne Pecena ◽

Doris Keye ◽

Kristin Conzelmann ◽

Dietrich Grasshoff ◽

Peter Maschke ◽

...

Keyword(s):

Predictive Validity ◽

Selection Procedure ◽

Air Traffic ◽

Performance Criteria ◽

Training Phase ◽

Air Traffic Controller ◽

Training Performance ◽

Navigation Service ◽

German Aerospace ◽

Training Success

The job of an air traffic controller (ATCO) is very specific and demanding. The assessment of potential suitable candidates requires a customized and efficient selection procedure. The German Aerospace Center DLR conducts a highly selective, multiple-stage selection procedure for ab initio ATCO applicants for the German Air Navigation Service Provider DFS. Successful applicants start their training with a training phase at the DFS Academy and then continue with a unit training phase in live traffic. ATCO validity studies are scarcely reported in the international scientific literature and have mainly been conducted in a military context with only small and male samples. This validation study encompasses the data from 430 DFS ATCO trainees, starting with candidate selection and extending to the completion of their training. Validity analyses involved the prediction of training success and several training performance criteria derived from initial training. The final training success rate of about 79% was highly satisfactory and higher than that of other countries. The findings demonstrated that all stages of the selection procedure showed predictive validity toward training performance. Among the best predictors were scores measuring attention and multitasking ability, and ratings on general motivation from the interview.

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