scholarly journals Designing High-Freedom Responsive Feeder Transit System with Multitype Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Zhengwu Wang ◽  
Jie Yu ◽  
Wei Hao ◽  
Tao Chen ◽  
Yi Wang
Keyword(s):  
Optimization Design ◽  
Programming Model ◽  
Supply And Demand ◽  
Heuristic Method ◽  
Service Area ◽  
Mixed Integer ◽  
Transit System ◽  
Last Mile ◽  
Feeder Transit ◽  
Vehicle Routes

The last mile travelling problem is the most challenging part when using public transit. This study designs a high-freedom responsive feeder transit (HFRFT) system to serve at the transfer station, given vehicle routes, departure time, and service area based on demand. The proposed feeder transit system employs a travelling mode with multitype vehicles. In order to improve the operation of the HFRFT system, the optimization design methods are suggested for vehicle routes, scheduling, and service area. A mixed integer programming model and its hybrid of a metaheuristic algorithm are proposed to efficiently and integrally solve the vehicle routes and scheduling parameters according to the reservation requirements. A heuristic method is proposed to optimize the service area based on the equilibrium of system supply and demand. Case studies show that the mixed running mode of multiple models can significantly improve the seat utilization, which can also significantly reduce the number of departures and the average travel distance per passenger. The proposed service area optimization method is proved to be feasible to improve the last mile travel.

scholarly journals Modeling the Scheduling Problem in Cellular Manufacturing Systems Using Genetic Algorithm as an Efficient Meta-Heuristic Approach

2021 ◽  
Author(s):  
Amin Rezaeipanah ◽  
Musa Mojarad
Keyword(s):  
Genetic Algorithm ◽  
Manufacturing Systems ◽  
Cellular Manufacturing ◽  
Programming Model ◽  
Heuristic Method ◽  
Cell Formation ◽  
Mixed Integer ◽  
Test Problems ◽  
Cellular Manufacturing Systems ◽  
Machine Grouping

This paper presents a new, bi-criteria mixed-integer programming model for scheduling cells and pieces within each cell in a manufacturing cellular system. The objective of this model is to minimize the makespan and inter-cell movements simultaneously, while considering sequence-dependent cell setup times. In the CMS design and planning, three main steps must be considered, namely cell formation (i.e., piece families and machine grouping), inter and intra-cell layouts, and scheduling issue. Due to the fact that the Cellular Manufacturing Systems (CMS) problem is NP-Hard, a Genetic Algorithm (GA) as an efficient meta-heuristic method is proposed to solve such a hard problem. Finally, a number of test problems are solved to show the efficiency of the proposed GA and the related computational results are compared with the results obtained by the use of an optimization tool.

Single machine earliness/tardiness scheduling problem with grey processing times and the grey common due date

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Oğuzhan Ahmet Arık
Keyword(s):  
Programming Model ◽  
Heuristic Method ◽  
Mixed Integer ◽  
Grey Theory ◽  
Scheduling Problem ◽  
Due Date ◽  
Content Type ◽  
Common Due Date ◽  
Processing Times ◽  
Uncertainty Of Parameters

PurposeThis paper presents a mixed-integer programming model for a single machine earliness/tardiness scheduling problem where the objective is to minimize total earliness/tardiness duration when the uncertainty of parameters such as processing times and due date is coded with grey numbers.Design/methodology/approachGrey theory and grey numbers are used for illustrating the uncertainty of parameters in processing times and common due date, where the objective is to minimize the total earliness/tardiness duration. The paper proposes a 0–1 mathematical model for the problem and an effective heuristic method for the problem by using expected processing times for ordering jobs.FindingsThe uncertainty of the processing times and common due date are encoded with grey numbers and a position-dependent mixed-integer mathematical programming model is proposed for the problem in order to minimize total grey earliness/tardiness duration of jobs having grey processing times and a common due date. By using expected processing times for ranking grey processing times, V-shaped property of the problem and an efficient heuristic method for the problem are proposed. Solutions obtained from the heuristic method show that the heuristic is effective. The experimental study also reveals that while differences between upper and lower bounds of grey processing times decrease, the proposed heuristic's performance decreases.Originality/valueThe grey theory and grey numbers have been rarely used as machine scheduling problems. Therefore, this study provides an important contribution to the literature.

scholarly journals Multi-objective optimization model for planning metro-based underground logistics system network: Nanjing case study

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Xiliang Sun ◽  
Wanjie Hu ◽  
Xiaolong Xue ◽  
Jianjun Dong
Keyword(s):  
Programming Model ◽  
Freight Transport ◽  
Optimization Techniques ◽  
Economic Feasibility ◽  
Environmental Cost ◽  
Mixed Integer ◽  
Logistics System ◽  
Transit System ◽  
Multi Objective ◽  
Good Ability

<p style='text-indent:20px;'>Utilizing rail transit system for collaborative passenger-and-freight transport is a sustainable option to conquer urban congestion. This study proposes effective modeling and optimization techniques for planning a city-wide metro-based underground logistics system (M-ULS) network. Firstly, a novel metro prototype integrating retrofitted underground stations and newly-built capsule pipelines is designed to support automated inbound delivery from urban logistics gateways to in-city destinations. Based on four indicators (i.e. unity of freight flows, regional accessibility, environmental cost-saving, and order priority), an entropy-based fuzzy TOPSIS evaluation model is proposed to select appropriate origin-destination flows for underground freight transport. Then, a mixed integer programming model, with a well-matched solution framework combining multi-objective PSO algorithm and A* algorithm, are developed to optimize the location-allocation-routing (LAR) decisions of M-ULS network. Finally, real-world simulation based on Nanjing metro case is conducted for validation. The best facility configurations and flow assignments of the three-tier M-ULS network are reported in details. Results confirm that the proposed algorithm has good ability in providing high-quality Pareto-optimal LAR decisions. Moreover, the Nanjing M-ULS project shows strong economic feasibility while bringing millions of Yuan of annual external benefit to the society and environment.</p>

scholarly journals Designing a clothing supply chain network considering pricing and demand sensitivity to discounts and advertisement

2020 ◽  
Author(s):  
Mohammad Mahdi Paydar ◽  
Marjan Olfati ◽  
chefi Triki
Keyword(s):  
Supply Chain ◽  
Programming Model ◽  
Rapid Development ◽  
Supply And Demand ◽  
Clothing Industry ◽  
Sensitivity Analyses ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Total Profit ◽  
Demand Sensitivity

These days, clothing companies are becoming more and more developed around the world. Due to the rapid development of these companies, designing an efficient clothing supply chain network can be highly beneficial, especially with the remarkable increase in demand and uncertainties in both supply and demand. In this study, a bi-objective stochastic mixed-integer linear programming model is proposed for designing the supply chain of the clothing industry. The first objective function maximizes total profit and the second one minimizes downside risk. In the presented network, the initial demand and price are uncertain and are incorporated into the model through a set of scenarios. To solve the bi-objective model, weighted normalized goal programming is applied. Besides, a real case study for the clothing industry in Iran is proposed to validate the presented model and developed method. The obtained results showed the validity and efficiency of the current study. Also, sensitivity analyses are conducted to evaluate the effect of several important parameters, such as discount and advertisement, on the supply chain .  The results indicate that considering the optimal amount for discount parameter can conceivably enhance total profit by about 20% compared to the time without this discount scheme. When we take the optimized parameter into account for advertisement, 12% is obtained for the total profit. Based on our findings, the more the expected profit value, the higher the total amount of total profit and risk.  The results of this research also provide some interesting managerial insights for managers.

Operator- and user-based rebalancing strategy for bike-sharing systems

2021 ◽  
pp. 1-12
Author(s):  
Peng-Sheng You ◽  
Yi-Chih Hsieh
Keyword(s):  
Dynamic Pricing ◽  
Programming Model ◽  
Supply And Demand ◽  
Planning Horizon ◽  
Sensitivity Analyses ◽  
Mixed Integer ◽  
Time Problem ◽  
Bike Sharing ◽  
Total Profit ◽  
The Impact

Leveraging their networks, bike rental companies usually provide customers with services for renting and returning bikes at different bike stations. Over time, however, rental networks may encounter problems with unbalanced bike stocks. The potential imbalance between supply and demand at bike stations may result in lost sales for stations with relatively high demand and underutilization for stations with relatively low demand. This paper proposed a constrained mixed-integer programming model that uses operator-based redistribution and user-based price approach to rebalance bikes across bike stations. This paper aims to maximize total profit over a planning horizon by determining operator-based bike transfers and dynamic pricing. The proposed model is a non-deterministic polynomial-time problem, and thus, a heuristic was developed based on linear programming and evolutionary computation to perform model solving. Numerical experiments reveal that the proposed method performed better than Lingo, a well-known commercial software. Sensitivity analyses were also performed to investigate the impact of changes in system parameters on computational results.

scholarly journals Optimization of Humanitarian Aid Distribution in Case of an Earthquake and Tsunami in the City of Iquique, Chile

2022 ◽  
Vol 14 (2) ◽  
pp. 819
Author(s):  
Antonia Ilabaca ◽  
Germán Paredes-Belmar ◽  
Pamela P. Alvarez
Keyword(s):  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Humanitarian Aid ◽  
Vulnerability Index ◽  
Mixed Integer ◽  
Routing Problem ◽  
Integer Linear Programming Model ◽  
The City ◽  
Vehicle Routes

In this paper, we introduce, model, and solve a clustered resource allocation and routing problem for humanitarian aid distribution in the event of an earthquake and subsequent tsunami. First, for the preparedness stage, we build a set of clusters to identify, classify, sort, focus, and prioritize the aid distribution. The clusters are built with k-means method and a modified version of the capacitated p-median model. Each cluster has a set of beneficiaries and candidate delivery aid points. Second, vehicle routes are strategically determined to visit the clusters for the response stage. A mixed integer linear programming model is presented to determine efficient vehicle routes, minimizing the aid distribution times. A vulnerability index is added to our model to prioritize aid distribution. A case study is solved for the city of Iquique, Chile.

scholarly journals Metodología para creación de rutas alimentadoras en sistemas de transporte masivo

2017 ◽  
Vol 26 (45) ◽  
Author(s):  
Daniela Ospina-Toro ◽  
Eliana Mirledy Toro-Ocampo ◽  
Ramón Alfonso Gallego-Rendón
Keyword(s):  
Programming Model ◽  
Methodological Approach ◽  
Exact Algorithm ◽  
Set Partitioning ◽  
Branch And Cut ◽  
Mixed Integer ◽  
Location Routing Problem ◽  
Transit System ◽  
Routing Problem ◽  
Location Routing

This paper proposes a methodology to identify feeder routes for areas disconnected to the Mass Transit System (MTS), in order to propose an alternative solution to the deficit in the number of passengers carried. The proposed methodology consists of two steps: (1) structuring scenarios for areas not connected to the transport system and (2) combining heuristic and exact techniques to solve the feeding routes problem considering in the restrictions the path length and passengers vehicle capacity.  To model the problem, a comparison with the Location Routing problem is established, which is usually applied to freight transport problems. The methodology proposed is a math-heuristic combining the Lin-Kernighan-Helsgaun algorithm (LKH) and the Clark and Wright’s Savings heuristic with the Branch-and-Cut exact algorithm, which is applied into a Mixed Integer Linear Programming model (MILP), also known as a Set Partitioning model (SP) for LRP. This methodological approach is validated with real instances considering locations in Pereira (Megabús), where some areas disconnected to the Central-Occidental Metropolitan Area System (AMCO) of Pereira, located in Colombia's Coffee Axis are considered.

Analysis on the Penetration Level of Wind Farm Considering Transient Stability Constraint and Uncertainty of Wind Power

2020 ◽  
Vol 13 (7) ◽  
pp. 1078-1086
Author(s):  
Bai Hao ◽  
Huang Andi ◽  
Zhou Changcheng
Keyword(s):  
Wind Power ◽  
Energy Function ◽  
Wind Farm ◽  
Transient Stability ◽  
Programming Model ◽  
Forecast Error ◽  
Credibility Theory ◽  
Mixed Integer ◽  
Stability Constraint ◽  
Level Problem

Background: The penetration level of a wind farm with transient stability constraint and static security constraint has been a key problem in wind power applications. Objective: The study explores maximum penetration level problem of wind considering transient stability constraint and uncertainty of wind power out, based on credibility theory and corrected energy function method. Methods: According to the corrected energy function, the transient stability constraint of the power grid is transferred to the penetration level problem of a wind farm. Wind speed forecast error is handled as a fuzzy variable to express the uncertainty of wind farm output. Then this paper builds a fuzzy chance-constrained model to calculate wind farm penetration level. To avoid inefficient fuzzy simulation, the model is simplified to a mixed integer linear programming model. Results: The results validate the proposed model and investigate the influence of grid-connection node, wind turbine characteristic, fuzzy reliability index, and transient stability index on wind farm penetration level. Conclusion: The result shows that the model proposed in this study can consider the uncertainty of wind power out and establish a quantitative transient stability constraint to determine the wind farm penetration level with a certain fuzzy confidence level.

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