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 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

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.

Epidemics Between Bailey and Reed-Frost: A Stochastic Version of the Kermack and Mckendrick Model

1997 ◽  
Vol 05 (04) ◽  
pp. 489-508 ◽  
Author(s):  
J. L. W. Gielen
Keyword(s):  
Deterministic Model ◽  
Density Functions ◽  
Final Size ◽  
Stochastic Description ◽  
Arrival Times ◽  
Stochastic Version ◽  
Source Of Infection ◽  
Proposed Model ◽  
Stochastic Epidemic ◽  
The Given

A model is developed that describes evolution with respect to time of an infectious disease introduced into a population of susceptibles. The proposed model incorporates at one end Bailey's simple stochastic epidemic and at the other end the Reed-Frost chain-binomial models and is the natural stochastic analogue of Kermack and McKendrick's deterministic model. The epidemic process is characterized by the size of the population and by two infectivity functions. The first one relates to a time dependent outside source of infection. The second one describes the infectivity of an individual as a function of his age-of-infection, that is the time elapsed since his own infection. The proposed model consists of a set of partial differential equations which governs, steered by the given infectivity functions, the evolution with respect to time of a set of density functions. These density functions deliver a complete stochastic description of the infectious-age structure of the population at any moment of time. An expression for the size of the epidemic, that is the probability distribution of the number of infectives, as a function of time follows. Also expressions for the expected arrival times of infectives, useful for the inverse problem, are developed. By letting time tend to infinity earlier results for the final size of the epidemic are confirmed.

Coordination of Feeder Bus Schedule with Train Service at Integrated Transport Hubs

2017 ◽  
Vol 2648 (1) ◽  
pp. 103-110 ◽  
Author(s):  
Xueping Dou ◽  
Xiaolin Gong ◽  
Xiucheng Guo ◽  
Tao Tao
Keyword(s):  
Urban Rail Transit ◽  
Operating Costs ◽  
Mixed Integer ◽  
Decision Variable ◽  
Coordination Problem ◽  
Schedule Coordination ◽  
Feeder Bus ◽  
Minlp Model ◽  
Bus Service ◽  
Bus Schedule

This paper proposes a schedule coordination method for transfer problems between an urban rail transit service and its feeder bus service. For given train schedules, a novel mixed-integer nonlinear programming (MINLP) model is formulated to obtain a coordinated bus schedule with the objective of minimizing the weighted sum of passenger transfer costs and bus operating costs. The queuing process for transfer passengers at the transport hubs, which is attributed to both high transfer volumes and limited bus capacity, is discussed and considered in the coordination problem. The vital decision variable is the terminal departure time of each target feeder bus trip within a certain time period. A hybrid solution method that integrates heuristic and enumerative algorithms was developed to solve the MINLP model, and numerical experiments were conducted for different scenarios. The results indicate that the feeder bus schedule coordinated by the developed model is capable of substantially reducing the transfer waiting time for train passengers with a slight increase in bus operating costs.

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.

scholarly journals A novel mathematical formulation for solving the dynamic and discrete berth allocation problem by using the Bee Colony Optimisation algorithm

2020 ◽  
Author(s):  
Luigi Pio Prencipe ◽  
Mario Marinelli
Keyword(s):  
Mathematical Formulation ◽  
Real Data ◽  
Allocation Problem ◽  
Mixed Integer ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Solution Approach ◽  
Bee Colony ◽  
Proposed Model ◽  
Berth Scheduling

AbstractBerth allocation is one of the crucial points for efficient management of ports. This problem is complex due to all possible combinations for assigning ships to available compatible berths. This paper focuses on solving the Berth Allocation Problem (BAP) by optimising port operations using an innovative model. The problem analysed in this work deals with the Discrete and Dynamic Berth Allocation Problem (DDBAP). We propose a novel mathematical formulation expressed as a Mixed Integer Linear Programming (MILP) for solving the DDBAP. Furthermore, we adapted a metaheuristic solution approach based on the Bee Colony Optimisation (BCO) for solving large-sized combinatorial BAPs. In order to assess the solution performance and efficiency of the proposed model, we introduce a new set of instances based on real data of the Livorno port (Italy), and a comparison between the BCO algorithm and CPLEX in solving the DDBAP is performed. Additionally, the application of the proposed model to a real berth scheduling (Livorno port data) and a comparison with the Ant Colony Optimisation (ACO) metaheuristic are carried out. Results highlight the feasibility of the proposed model and the effectiveness of BCO when compared to both CPLEX and ACO, achieving computation times that ensure a real-time application of the method.

scholarly journals Improving the Efficiency of Medical Services Systems: A New Integrated Mathematical Modeling Approach

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Davood Shishebori ◽  
Mohammad Saeed Jabalameli
Keyword(s):  
Medical Service ◽  
Programming Model ◽  
Critical Role ◽  
Transportation Cost ◽  
Mixed Integer ◽  
Medical Services ◽  
Practical Case ◽  
Efficient Design ◽  
Proposed Model ◽  
Failure Cost

Nowadays, the efficient design of medical service systems plays a critical role in improving the performance and efficiency of medical services provided by governments. Accordingly, health care planners in countries especially with a system based on a National Health Service (NHS) try to make decisions on where to locate and how to organize medical services regarding several conditions in different residence areas, so as to improve the geographic equity of comfortable access in the delivery of medical services while accounting for efficiency and cost issues especially in crucial situations. Therefore, optimally locating of such services and also suitable allocating demands them, can help to enhance the performance and responsiveness of medical services system. In this paper, a multiobjective mixed integer nonlinear programming model is proposed to decide locations of new medical system centers, link roads that should be constructed or improved, and also urban residence centers covered by these medical service centers and link roads under investment budget constraint in order to both minimize the total transportation cost of the overall system and minimize the total failure cost (i.e., maximize the system reliability) of medical service centers under unforeseen situations. Then, the proposed model is linearized by suitable techniques. Moreover, a practical case study is presented in detail to illustrate the application of the proposed mathematical model. Finally, a sensitivity analysis is done to provide an insight into the behavior of the proposed model in response to changes of key parameters of the problem.

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