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Documents in2 Corresponding author Abstract This paper surveys a large variety of mathematical models and up-to-date Solution techniques developed for solving a general flight gate scheduling problem that deals with assigning difFerent aircraft activities (arrival, departure and intermediate parking) to distinct aircraft stands or gates. The aim of the work is both to present various models and Solution techniques which are available in nowadays literature and to give a general idea about new open problems that arise in practise. We restrict the scope of the paper to flight gate Management without touching scheduling of ground handling Operations.Keywords: flight gate scheduling, assignment of aircraft activities to terminals, survey of models and algorithms.
T his paper considers the problem of assigning flights to airport gates. We examine the general case in which an aircraft serving a flight may be assigned to different gates for arrival and departure processing and for optional intermediate parking. Restrictions to this assignment include gate closures and shadow restrictions, i.e., the situation in which certain gate assignments may cause the blocking of neighboring gates. The objectives include maximization of the total assignment preference score, minimization of the number of unassigned flights during overload periods, minimization of the number of tows, as well as maximization of the robustness of the resulting schedule with respect to flight delays. We are presenting a simple transformation of the flight-gate scheduling (FGS) problem to a graph problem, i.e., the clique partitioning problem (CPP). The algorithm used to solve the CPP is a heuristic based on the ejection chain algorithm by Dorndorf and Pesch [Dorndorf, U., E. Pesch. 1994. Fast clustering algorithms. ORSA J. Comput. 6 141-153]. This leads to a very effective approach for solving the original problem.
Resource-constrained project scheduling with generalised precedence constraints is a very general scheduling model with applications in areas such as make-to-order production planning. We describe a time-oriented branch-and-bound algorithm that uses constraint-propagation techniques which actively exploit the temporal and resource constraints of the problem in order to reduce the search space. Extensive computational experiments with systematically generated test problems show that the algorithm solves more problems to optimality than other exact solution procedures which have recently been proposed, and that the truncated version of the algorithm is also a very good heuristic.project scheduling, resource constraints, time windows, generalised precedence constraints, branch and bound, constraint propagation
This paper considers the problem of partitioning the vertices of a weighted complete graph into cliques of unbounded size and number, such that the sum of the edge weights of all cliques is maximized. The problem is known as the clique-partitioning problem and arises as a clustering problem in qualitative data analysis. A simple greedy algorithm is extended to an ejection chain heuristic leading to optimal solutions in all practical test problems known from literature. The heuristic is used to compute an initial lower bound as well as to guide branching in a branch and bound algorithm which is superior to present exact methods. Empirical data for all three algorithms are reported. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
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