scholarly journals Mixed integer nonlinear programming for three-dimensional aircraft conflict avoidance

2018 ◽  
Author(s):  
Junling Cai ◽  
Ning Zhang
Keyword(s):  
Traffic Management ◽  
Three Dimensional ◽  
Mixed Integer ◽  
Conflict Avoidance ◽  
Non Linear Programming ◽  
Proposed Model ◽  
Minlp Model ◽  
Heading Angle ◽  
Comparison Of The Results ◽  
Aircraft Conflict Avoidance

The problem of aircraft conflict avoidance for Air Traffic Management systems is studied. In the scenario, aircraft are considered to fly within a shared three-dimensional airspace and not allowed to approach close less than a minimum safe separation during their flights in order to avoid various conflicts. This paper proposes a formulation of the three-dimensional conflict avoidance problem as a Mixed Integer Non-Linear Programming (MINLP) model where aircraft are allowed to change both their heading angle and velocity simultaneously to keep the separation. The validity of the proposed model is demonstrated by a comparison of the results from the MINLP model and the previous conflict avoidance models with one maneuver of the heading angle or the velocity. The numerical studies show that the MINLP model improves the efficiency of computation and maintain the safety of flights even by using a standard global optimization solver

scholarly journals Mixed integer nonlinear programming for three-dimensional aircraft conflict avoidance

2018 ◽  
Author(s):  
Junling Cai ◽  
Ning Zhang
Keyword(s):  
Traffic Management ◽  
Three Dimensional ◽  
Mixed Integer ◽  
Conflict Avoidance ◽  
Non Linear Programming ◽  
Proposed Model ◽  
Minlp Model ◽  
Heading Angle ◽  
Comparison Of The Results ◽  
Aircraft Conflict Avoidance

The problem of aircraft conflict avoidance for Air Traffic Management systems is studied. In the scenario, aircraft are considered to fly within a shared three-dimensional airspace and not allowed to approach close less than a minimum safe separation during their flights in order to avoid various conflicts. This paper proposes a formulation of the three-dimensional conflict avoidance problem as a Mixed Integer Non-Linear Programming (MINLP) model where aircraft are allowed to change both their heading angle and velocity simultaneously to keep the separation. The validity of the proposed model is demonstrated by a comparison of the results from the MINLP model and the previous conflict avoidance models with one maneuver of the heading angle or the velocity. The numerical studies show that the MINLP model improves the efficiency of computation and maintain the safety of flights even by using a standard global optimization solver

Feeder Bus Timetable Design and Vehicle Size Setting in Peak Hour Demand Conditions

2019 ◽  
Vol 2673 (10) ◽  
pp. 321-332 ◽  
Author(s):  
Xueping Dou ◽  
Qiang Meng
Keyword(s):  
Mixed Integer ◽  
Arrival Times ◽  
Non Linear Programming ◽  
Bee Colony ◽  
Proposed Model ◽  
Feeder Bus ◽  
Minlp Model ◽  
Failure Cost ◽  
Set Up ◽  
The Given

This study proposes a solution to the feeder bus timetabling problem, in which the terminal departure times and vehicle sizes are simultaneously determined based on the given transfer passengers and their arrival times at a bus terminal. The problem is formulated as a mixed integer non-linear programming (MINLP) model with the objective of minimizing the transfer waiting time of served passengers, the transfer failure cost of non-served passengers, and the operating costs of bus companies. In addition to train passengers who plan to transfer to buses, local passengers who intend to board buses are considered and treated as passengers from virtual trains in the proposed model. Passenger attitudes and behaviors toward the waiting queue caused by bus capacity constraints in peak hour demand conditions are explicitly embedded in the MINLP model. A hybrid artificial bee colony (ABC) algorithm is developed to solve the MINLP model. Various experiments are set up to account for the performance of the proposed model and solution algorithm.

scholarly journals End-to-End Delay QoS Attribute-Based Bundling Strategy of Wireless Improved Reverse Charging Network Pricing Model

2021 ◽  
Vol 6 (1) ◽  
pp. 30
Author(s):  
Fitri Maya Puspita ◽  
Ayu Wulandari ◽  
Evi Yuliza ◽  
Robinson Sitepu ◽  
Yunita Yunita
Keyword(s):  
Optimal Solution ◽  
Internet Usage ◽  
Mixed Integer ◽  
Satisfaction Level ◽  
Pricing Model ◽  
Service Networks ◽  
Service Network ◽  
Non Linear Programming ◽  
End To End Delay ◽  
Minlp Model

In this article, a multi-link internet reverse charging (IRC) scheme model in a multi-service network with the addition of a bundling strategy is proposed. Reverse charging schemes in multi-link and multi-service networks are rarely discussed in previous studies. This financing scheme is designed with the aim of maximizing service provider profits by minimizing internet usage costs. The basic cost and satisfaction level of the service provided by the ISP is focused on this effort. The model formed in this study is a Mixed Integer Non-Linear Programming (MINLP) model that is completed using software LINGO 13.0. This problem comprises two cases, when α case as a parameter and β as a parameter and or variable with sub–cases   increases in usage based financing schemes. Thus, the results obtained can be a consideration for ISPs in determining the price of services that can support an ISP. The updated IRC model provides a more optimal solution than the original IRC model.

DESIGNING CONTAINER SHIPPING NETWORK UNDER CHANGING DEMAND AND FREIGHT RATES

Transport ◽  
2010 ◽  
Vol 25 (1) ◽  
pp. 56-57 ◽  
Author(s):  
Chao Chen ◽  
Qingcheng Zeng
Keyword(s):  
Mixed Integer ◽  
Container Shipping ◽  
Suggested Model ◽  
Analytical Methodology ◽  
Non Linear Programming ◽  
Freight Rates ◽  
Proposed Model ◽  
Empty Container Repositioning ◽  
Average Unit ◽  
Three Stages

This paper focuses on the optimization of container shipping network and its operations under changing cargo demand and freight rates. The problem is formulated as a mixed integer non-linear programming problem (MINP) with an objective of maximizing the average unit ship-slot profit at three stages using analytical methodology. The issues such as empty container repositioning, ship-slot allocating, ship sizing, and container configuration are simultaneously considered based on a series of the matrices of demand for a year. To solve the model, a bi-level genetic algorithm based method is proposed. Finally, numerical experiments are provided to illustrate the validity of the proposed model and algorithms. The obtained results show that the suggested model can provide a more realistic solution to the issues on the basis of changing demand and freight rates and arrange a more effective approach to the optimization of container shipping network structures and operations than does the model based on the average demand.

scholarly journals Cross-docks scheduling with multiple doors using fuzzy approach

2020 ◽  
Vol 79 (ET.2020) ◽  
pp. 1-18
Author(s):  
Mitra Movassaghi
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Programming Model ◽  
Linear Programming Model ◽  
Mixed Integer ◽  
Non Linear Programming ◽  
Cross Docking ◽  
Proposed Model ◽  
Delivery Routes ◽  
Programming Techniques

One of the most important practices in logistics is Cross-Docking which sets its goals as inventory reduction and customer satisfaction increase. Customers receive goods through docks. Docks are responsible to provide a place for goods before being delivered to the customers. Then, these materials are directly loaded into outbound trucks with little or no storage in between to send to customers in the shortest possible time. This paper is mainly aimed at introducing a mixed integer, non-linear programming model to solve scheduling several cross-docking problems. The proposed model is highly facilitated to allocate the most optimal destinations to storage doors and truck scheduling in docks while selecting the collection and delivery routes. Using optimization approaches at uncertainty conditions is also of great importance. Mathematical programming techniques vividly fail to solve transportation problems that include fuzzy objective function coefficients. A fuzzy multi-objective linear programming model is proposed to solve the transportation decision-making with fuzzy objective function coefficients.

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