Every aircraft, military or civilian, must be grounded for maintenance after it has completed a certain number of flight hours since its last maintenance check. In this paper, we address the problem of deciding which available aircraft should fly and for how long, and which grounded aircraft should perform maintenance operations, in a group of aircraft that comprise a combat unit. The objective is to achieve maximum availability of the unit over the planning horizon. We develop a multiobjective optimization model for this problem, and we illustrate its application and solution on a real life instance drawn from the Hellenic Air Force. We also propose two heuristic approaches for solving large scale instances of the problem. We conclude with a discussion that gives insight into the behavior of the model and of the heuristics, based on the analysis of the results obtained.Keywords: fleet availability, flight and maintenance planning, multiobjective mixed integer linear program, military aircraft.
We develop a model of a failure-prone, bufferless, paced, automatic transfer line in which material flows through a number of workstations in series, receiving continuous processing along each workstation. When a workstation fails, it stops operating, and so do all the other workstations upstream of it. The quality of the material trapped in the stopped workstations deteriorates with time. If this material remains immobilized beyond a certain critical time, its quality becomes unacceptable and it must be scrapped. We develop analytical expressions for important system performance measures for two cases. In the first case, the in-process material has no memory of the quality deterioration that it experienced during previous stoppages, whereas in the second case it has. In both cases, we assume that the workstation uptimes and downtimes follow memoryless distributions. We use the analytical expressions to numerically study the effect of system parameters on system performance. To evaluate the memoryless assumption, we compare the performance of the original model to that of a modified model in which the workstation downtimes do not follow memoryless distributions. The performance of the modified model is obtained via simulation.transfer line, material scrapping, performance evaluation
In this paper, we address the design of a joint energy -reserve electricity market with non-convexities which are due to the fixed costs and capacity constraints of the generation units.
Motivated by the relevant literature [1]-[5], we state a bid recovery mechanism that applies to the day-ahead scheduling problem, which is modeled as a mixed-integer linear programming problem. However, the particularly complex nature of the problem, especially if we consider it in its full scale, makes it extremely difficult if not impossible to analytically assess the market operation, under various market designs. Therefore, we proceed to an empirical analysis that aims to provide useful insight in evaluating the incentive compatibility of pricing and compensation schemes based on marginal pricing theory. In order to understand the bidding behavior of the participants and exhibit the proposed methodology, we present an illustrative example, based on Greece's day-ahead energy -reserve market.
Every aircraft, military or civilian, must be grounded for maintenance after it has completed a certain number of flight hours since its last maintenance check. Flight and maintenance planning of military aircraft addresses the problem of deciding which available aircraft to fly and for how long, and which grounded aircraft to perform maintenance operations on, in a set of aircraft that comprise a combat unit. The objective is to achieve maximum availability of the unit over the planning horizon. In this work, we develop a biobjective optimization model of the flight and maintenance planning problem, and we illustrate its application and solution on a real life instance drawn from the Hellenic Air Force. We formulate the flight and maintenance planning problem as a mixed integer linear program, with two objectives: total number of available aircraft and total residual flight time. The residual flight time of an available aircraft is defined as the total remaining time that this aircraft can fly, until it has to be grounded for maintenance check. For the solution of the problem we apply the weighted sums approach and lexicographic optimization. By comparing and analyzing the solutions obtained, we get insight into the behavior of the model. We conclude with a discussion based on these results and suggestions on how the model can be extended in the future.
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