scholarly journals Operation optimizing for minimizing passenger travel time cost and operating cost with time-dependent demand and skip-stop patterns: Nonlinear integer programming model with linear constraints

2021 ◽  
Vol 9 ◽  
pp. 100309
Author(s):  
Junru Zhao ◽  
Mao Ye ◽  
Zhiqiang Yang ◽  
Zongyi Xing ◽  
ZiHan Zhang
Keyword(s):  
Integer Programming ◽  
Travel Time ◽  
Programming Model ◽  
Operating Cost ◽  
Linear Constraints ◽  
Time Dependent ◽  
Nonlinear Integer Programming ◽  
Time Cost ◽  
Passenger Travel ◽  
Dependent Demand

Paratransit Service Optimization for Special Events

2005 ◽  
Vol 1903 (1) ◽  
pp. 64-77
Author(s):  
Matthew G. Karlaftis ◽  
Konstantinos L. Kepaptsoglou ◽  
Antony Stathopoulos
Keyword(s):  
Integer Programming ◽  
Travel Time ◽  
Programming Model ◽  
Nonlinear Integer Programming ◽  
Time Constraints ◽  
Microsoft Excel ◽  
Integer Programming Model ◽  
Special Events ◽  
User Friendly ◽  
Service Optimization

Paratransit services can be useful for special events, especially when private vehicles are discouraged from approaching the event locations. During the Athens 2004 Olympics, such a shuttle service was planned to connect major Athens spots with athletic complexes. A mixed nonlinear integer programming model is developed for jointly obtaining optimal headways and vehicle types for such a paratransit service, given demand, resource, and travel time constraints. The model is incorporated into a user-friendly Microsoft Excel–based interface. An application of the model to the Athens 2004 Olympics and its results are presented and discussed.

scholarly journals Timetable Design for Minimizing Passenger Travel Time and Congestion for a Single Metro Line

2018 ◽  
Vol 30 (1) ◽  
pp. 21-33 ◽  
Author(s):  
Yi Shen ◽  
Gang Ren ◽  
Yang Liu
Keyword(s):  
Travel Time ◽  
Optimization Problem ◽  
Programming Model ◽  
Optimization Method ◽  
Flow State ◽  
Passenger Travel ◽  
Operation Period ◽  
Recursive Optimization ◽  
Timetable Optimization ◽  
Dependent Demand

This paper brings a proposal for a timetable optimization model for minimizing the passenger travel time and congestion for a single metro line under time-dependent demand. The model is an integer-programming model that systemically considers the passenger travel time, the capacity of trains, and the capacity of platforms. A multi-objective function and a recursive optimization method are presented to solve the optimization problem. Using the model we can obtain an efficient timetable with minimal passenger travel time and minimal number of congestion events on platforms. Moreover, by increasing the number of dispatches, the critical point from congestion state to free-flow state and the optimal timetable with minimal cost for avoiding congestion on platforms can be obtained. The effectiveness of the model is evaluated by a real example. A half-regular timetable with fixed headways in each operation period and an irregular timetable with unfixed headway are investigated for comparison.

scholarly journals Optimal placement design for picking and packing in distribution centers

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110106
Author(s):  
John Rios ◽  
Rodrigo Linfati ◽  
Daniel Morillo-Torres ◽  
Iván Derpich ◽  
Gustavo Gatica
Keyword(s):  
Optimal Allocation ◽  
Programming Model ◽  
Operating Cost ◽  
Nonlinear Integer Programming ◽  
Operating Costs ◽  
Optimal Placement ◽  
Distribution Centers ◽  
Suitable Space ◽  
Efficient Distribution

An efficient distribution center (DC) is one that receives, stores, picks and packs products into new logistics units and then dispatches them to points of sale at the minimal operating cost. The picking and packing processes represent the highest operating cost of a DC, and both require a suitable space for their operation. An effective coordination between these zones prevents bottlenecks and has a direct impact on the DC’s operational results. In the existing literature, there are no studies that optimize the distribution of the picking and packing areas simultaneously while also reducing operating costs. This article proposes an integer nonlinear integer programming model that minimizes order preparation costs. It does so by predicting customer demand based on historical data and defining the ideal area for picking and packing activities. The model is validated through a real case study of seven clients and fifteen products. It achieves a [Formula: see text] reduction in operating costs when the optimal allocation of the picking and packing areas is made.

scholarly journals Stop Plan of Express and Local Train for Regional Rail Transit Line

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Qin Luo ◽  
Yufei Hou ◽  
Wei Li ◽  
Xiongfei Zhang
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Programming Model ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Long Distance ◽  
Passenger Travel ◽  
Urban Rail ◽  
Proposed Model ◽  
Rail Line

The urban rail transit line operating in the express and local train mode can solve the problem of disequilibrium passenger flow and space and meet the rapid arrival demand of long-distance passengers. In this paper, the Logit model is used to analyze the behavior of passengers choosing trains by considering the sensitivity of travel time and travel distance. Then, based on the composition of passenger travel time, an integer programming model for train stop scheme, aimed at minimizing the total passenger travel time, is proposed. Finally, combined with a certain regional rail line in Shenzhen, the plan is solved by genetic algorithm and evaluated through the time benefit, carrying capacity, and energy consumption efficiency. The simulation result shows that although the capacity is reduced by 6 trains, the optimized travel time per person is 10.34 min, and the energy consumption is saved by about 16%, which proves that the proposed model is efficient and feasible.

scholarly journals The unit train make-up scheme for loaded direction in the heavy haul railway

2019 ◽  
Vol 1 (1) ◽  
pp. 30-44 ◽  
Author(s):  
Yuqiang Wang ◽  
Yuguang Wei ◽  
Hua Shi ◽  
Xinyu Liu ◽  
Liyuan Feng ◽  
...  
Keyword(s):  
Integer Programming ◽  
Design Methodology ◽  
Arrival Time ◽  
Programming Model ◽  
Nonlinear Integer Programming ◽  
Content Type ◽  
Proposed Model ◽  
Heavy Haul ◽  
Heavy Haul Railway

Purpose The purpose of this paper is to study the unit train make-up scheme for loaded direction in the heavy haul railway. Design/methodology/approach A 0-1 nonlinear integer programming model with the aim of minimizing the idling period between actual train arrival time and expected train arrival time for all loaded unit trains are proposed. Findings The proposed model is applied into a case study based on Daqin heavy haul railway. Results show that the proposed model can offer operators an optimal unit train make-up scheme for loaded direction in heavy haul railway. Originality/value The proposed model can offer operators an optimal unit train make-up scheme for loaded direction in heavy haul railway.

scholarly journals A Nonlinear Integer Programming Model for Integrated Location, Inventory, and Routing Decisions in a Closed-Loop Supply Chain

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Hao Guo ◽  
Congdong Li ◽  
Ying Zhang ◽  
Chunnan Zhang ◽  
Yu Wang
Keyword(s):  
Supply Chain ◽  
Integer Programming ◽  
Facility Location ◽  
Vehicle Routing ◽  
Closed Loop ◽  
Programming Model ◽  
Nonlinear Integer Programming ◽  
Inventory Routing ◽  
Closed Loop Supply Chain ◽  
Integer Programming Model

Facility location, inventory management, and vehicle routing are three important decisions in supply chain management, and location-inventory-routing problems consider them jointly to improve the performance and efficiency of today’s supply chain networks. In this paper, we study a location-inventory-routing problem to minimize the total cost in a closed-loop supply chain that has forward and reverse logistics flows. First, we formulate this problem as a nonlinear integer programming model to optimize facility location, inventory control, and vehicle routing decisions simultaneously in such a system. Second, we develop a novel heuristic approach that incorporates simulated annealing into adaptive genetic algorithm to solve the model efficiently. Last, numerical analysis is presented to validate our solution approach, and it also provides meaningful managerial insight into how to improve the closed-loop supply chain under study.

Flight Flow Balanced Allocation in Terminal Airspace

2013 ◽  
Vol 441 ◽  
pp. 602-606
Author(s):  
Wei Jun Pan ◽  
Wen Bin Qiu ◽  
Rui Kang
Keyword(s):  
Integer Programming ◽  
Programming Model ◽  
Air Traffic ◽  
Nonlinear Integer Programming ◽  
Flight Delays ◽  
Air Traffic Controllers ◽  
Balanced Allocation ◽  
Airport Terminal ◽  
Flight Route ◽  
Better Than

A nonlinear integer programming model (NIPM) with constraints is proposed to solve the allocation of approach flight flow where ends with terminal airspace, an example of an airport terminal airspace is given, where the flow is accurately forecasted.Analysising flight delays, theres a conclusion: the results solved by NIPM is far better than the average allocation method, for the second-level airspace, NIPM can reduce two flight delays, and the allocation in each flight route tends to be equilibrium, NIPM can also provide air traffic controllers with accurate and reasonable allocation schedule.

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