In this paper, the problem of aircraft conflict avoidance is studied arising in Air Traffic Management systems. The initial configuration of all aircraft including position, velocities, heading angles, altitude and fl...
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ISBN:
(纸本)9781665440899
In this paper, the problem of aircraft conflict avoidance is studied arising in Air Traffic Management systems. The initial configuration of all aircraft including position, velocities, heading angles, altitude and flight trajectories are known, and they are assumed to fly within a shared three-dimensional airspace. The aim of the problem is to find an optimal conflict avoidance strategy for the aircraft so that various conflicts situations can be avoided. A conflict occurs when the relative distance between any pairs of aircraft is less than the minimal safe separation during their flights. In order to ensure the safety of aircraft flight, a mixed integer nonlinear programming model (MINLP) for solving the three-dimensional conflict avoidance problem involving multiple aircrafts is proposed in this paper, where the aircraft are allowed to change simultaneously heading angle and velocity to achieve the separation. The illustration verifies the effectiveness of the method. The optimal solution of the problem can be obtained easily in a small computational time by using a standard global optimization solver to solve the proposed MINLP model.
We present two new algorithms for convex mixed integer nonlinear programming (MINLP), both based on the well known Extended Cutting Plane (ECP) algorithm proposed by Weterlund and Petersson. Our first algorithm, Refin...
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We present two new algorithms for convex mixed integer nonlinear programming (MINLP), both based on the well known Extended Cutting Plane (ECP) algorithm proposed by Weterlund and Petersson. Our first algorithm, Refined Extended Cutting Plane (RECP), incorporates additional cuts to the MILP relaxation of the original problem, obtained by solving linear relaxations of NLP problems considered in the Outer Approximation algorithm. Our second algorithm, Linear programming based Branch-and-Bound (LP-BB), applies the strategy of generating cuts that is used in RECP, to the linear approximation scheme used by the LP/NLP based Branch-and-Bound algorithm. Our computational results show that RECP and LP-BB are highly competitive with the most popular MINLP algorithms from the literature, while keeping the nice and desirable characteristic of ECP, of being a first-order method.
In this paper,the problem of aircraft conflict avoidance is studied arising in Air Traffic Management *** initial configuration of all aircraft including position,velocities,heading angles,altitude and flight trajecto...
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In this paper,the problem of aircraft conflict avoidance is studied arising in Air Traffic Management *** initial configuration of all aircraft including position,velocities,heading angles,altitude and flight trajectories are known,and they are assumed to fly within a shared three-dimensional *** aim of the problem is to find an optimal conflict avoidance strategy for the aircraft so that various conflicts situations can be avoided.A conflict occurs when the relative distance between any pairs of aircraft is less than the minimal safe separation during their *** order to ensure the safety of aircraft flight,a mixed integer nonlinear programming model(MINLP) for solving the three-dimensional conflict avoidance problem involving multiple aircrafts is proposed in this paper,where the aircraft are allowed to change simultaneously heading angle and velocity to achieve the *** illustration verifies the effectiveness of the *** optimal solution of the problem can be obtained easily in a small computational time by using a standard global optimization solver to solve the proposed MINLP model.
The maneuvers of aircraft conflict avoidance are studied for air traffic management systems. In the scenario, aircraft are considered to operate flight within a shared airspace and cannot violate the minimum safe sepa...
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The maneuvers of aircraft conflict avoidance are studied for air traffic management systems. In the scenario, aircraft are considered to operate flight within a shared airspace and cannot violate the minimum safe separation that they must keep in flight in order to avoid various possible conflicts. This paper proposes a formulation of the conflict avoidance problem as a mixed integer nonlinear programming (MINLP) with the maneuver that aircraft are allowed to change velocity and altitude to maintain the separation. Numerical experiments are performed to demonstrate the validity of the proposed MINLP model by comparison with the previous conflict avoidance model with only velocity change, and the illustration indicated a significant improvement in the efficiency of the conflict resolution as well as the magnitude of velocity variation. The optimal solutions of the problem are easily obtained by using global optimization solver in a shorter computational time even for large-scale aircraft.
The separation of solid particles from gas-solid process streams is an important unit operation in many chemical processes. Out of the many different types of separation equipment that are used for gas-solid separatio...
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The separation of solid particles from gas-solid process streams is an important unit operation in many chemical processes. Out of the many different types of separation equipment that are used for gas-solid separation, cyclone separators are widely used for their operational flexibility, efficiency and capital cost. This study focused on the design of an optimal configuration for several cyclones used in a fertilizer plant. The granulation step in the fertilizer plant leads to using different size cyclones and a different number of cyclones in series or parallel or a mix of both arrangements. A mixed integer nonlinear programming (MINLP) model is formulated to find the best cyclone arrangement with the optimal number of cyclones and dimensions from several combinations of 1D3D and 2D2D cyclones arranged in parallel-series for a high volume and heavy loading of solid particles. The objective function was to minimize the total cost, including the operating cost and the capital cost. The results indicated that a maximum of 90% efficiency is achieved with a parallel-series arrangement of 1D3D and 2D2D cyclones to be an optimal configuration for the maximum reduction in pollution level.
The joint coordination of plug-in electric vehicles (PEVs) charging and grid power control is to minimize both PEVs' charging cost and energy generation cost in meeting both PEVs' power demands and power grid ...
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ISBN:
(纸本)9781538680995
The joint coordination of plug-in electric vehicles (PEVs) charging and grid power control is to minimize both PEVs' charging cost and energy generation cost in meeting both PEVs' power demands and power grid operational constraints. A bang-bang PEV charging strategy is adopted to exploit its simple online implementation, which requires computation of a mixed integer nonlinear programming problem (MINP) in binary variables of the PEV charging and continuous variables of the grid voltages. A novel solver for this challenging MINP is proposed. Its efficiency is shown by numerical simulations.
Optimal exact designs are problematic to find and study because there is no unified theory for determining them and studying their properties. Each has its own challenges and when a method exists to confirm the design...
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Optimal exact designs are problematic to find and study because there is no unified theory for determining them and studying their properties. Each has its own challenges and when a method exists to confirm the design optimality, it is invariably applicable to the particular problem only. We propose a systematic approach to construct optimal exact designs by incorporating the Cholesky decomposition of the Fisher Information Matrix in a mixed integer nonlinear programming formulation. As examples, we apply the methodology to find D- and A-optimal exact designs for linear and nonlinear models using global or local optimizers. Our examples include design problems with constraints on the locations or the number of replicates at the optimal design points.
In a mixed-integernonlinearprogramming problem, integer restrictions divide the feasible region into discontinuous feasible parts with different sizes. Evolutionary Algorithms (EAs) are usually vulnerable to being t...
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ISBN:
(数字)9781665467087
ISBN:
(纸本)9781665467087
In a mixed-integernonlinearprogramming problem, integer restrictions divide the feasible region into discontinuous feasible parts with different sizes. Evolutionary Algorithms (EAs) are usually vulnerable to being trapped in larger discontinuous feasible parts. In this work, an improved version of an Estimation of Distribution Algorithm (EDA) is developed, where two new operations are proposed. The first one establishes a link between the learning-based histogram model and the s-constrained method. Here, the constraint violation level of the s-constrained method is used to explore the smaller discontinuous parts and form a better statistical model. The second operation is the hybridization of the EDA with a mutation operator to generate offspring from both the global distribution information and the parent information. A benchmark is used to test the performance of the improved proposal. The results indicated that the proposed approach shows a better performance against other tested EAs. This new proposal solves to a great extent the influence of the larger discontinuous feasible parts, and improve the local refinement of the real variables.
Optimising crop planning in conjunction with intra-seasonal water allocation necessitates the use of daily water budget calculations to determine the timing and amount of irrigation events, which complicates the solut...
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Optimising crop planning in conjunction with intra-seasonal water allocation necessitates the use of daily water budget calculations to determine the timing and amount of irrigation events, which complicates the solution of the problem to global optimality. The main objective of this research was to compare the intra-seasonal water allocation of a mixed integer nonlinear programming (MINLP) model with that of differential evolution (DE), to allocate a limited amount of water while considering irrigable area and the irrigation schedule that will maximise the total gross margin. Results show that both solution procedures adhere to economic theory of water allocation under limited water supply. The conclusion is that the MINLP model most likely achieved very near global optimality as the solutions of the two models were very close to each other. DE holds promise to solve more complex models involving risk and multiple crops.
In this paper, a nonlinear model to maximize biomass production with specific nutritional quality is proposed. The model decides about kind of grasses and legumes to cultivate, quantities of each grasses and legumes c...
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In this paper, a nonlinear model to maximize biomass production with specific nutritional quality is proposed. The model decides about kind of grasses and legumes to cultivate, quantities of each grasses and legumes chosen, the use of resources, and the proper time of harvest at which the biomass with specific nutritional quality is maximized. Model works with sufficient information about biomass yield, nutrient content, water requirements and fertilizer requirements of several crops, and it can explore all possible harvest times and choose the right time in which biomass production is maximized with desired nutritional quality. Furthermore, the solution gives to the producers additional information on weekly irrigation plan and weekly fertilizers plan for m(2) of cultivated grass. The model was tested on six scenarios using GAMS and obtained solutions are the global solution in each scenario.
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