scholarly journals Optimization Method of Customized Shuttle Bus Lines under Random Condition

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 52
Author(s):  
Zhichao Sun ◽  
Kang Zhou ◽  
Xinzheng Yang ◽  
Xiao Peng ◽  
Rui Song
Keyword(s):  
Travel Time ◽  
Travel Demand ◽  
Operating Cost ◽  
Optimization Method ◽  
Routing Problem ◽  
Hybrid Intelligent Algorithm ◽  
Passenger Travel ◽  
Time Requirements ◽  
The Cost ◽  
Stochastic Constraints

Transit network optimization can effectively improve transit efficiency, improve traffic conditions, and reduce the pollution of the environment. In order to better meet the travel demands of passengers, the factors influencing passengers’ satisfaction with a customized bus are fully analyzed. Taking the minimum operating cost of the enterprise as the objective and considering the random travel time constraints of passengers, the customized bus routes are optimized. The K-means clustering analysis is used to classify the passengers’ needs based on the analysis of the passenger travel demand of the customized shuttle bus, and the time stochastic uncertainty under the operating environment of the customized shuttle bus line is fully considered. On the basis of meeting the passenger travel time requirements and minimizing the cost of service operation, an optimization model that maximizes the overall satisfaction of passengers and public transit enterprises is structured. The smaller the value of the objective function is, the lower the operating cost. When the value is negative, it means there is profit. The model is processed by the deterministic processing method of random constraints, and then the hybrid intelligent algorithm is used to solve the model. A stochastic simulation technique is used to train stochastic constraints to approximate uncertain functions. Then, the improved immune clonal algorithm is used to solve the vehicle routing problem. Finally, it is proved by a case that the method can reasonably and efficiently realize the optimization of the customized shuttle bus lines in the region.

Optimization of Multistage Machining Systems, Part 1: Mathematical Solution

1992 ◽  
Vol 114 (4) ◽  
pp. 524-531 ◽  
Author(s):  
J. S. Agapiou
Keyword(s):  
Optimization Problem ◽  
Cutting Parameters ◽  
Optimization Method ◽  
Idle Time ◽  
Optimization Techniques ◽  
Machining Parameters ◽  
Machining Time ◽  
Physical Constraints ◽  
Time Requirements ◽  
The Cost

The optimization problem for multistage machining systems has been investigated. Due to uneven time requirements at different stages in manufacturing, there could be idle times at various stations. It may be advantageous to reduce the values of machining parameters in order to reduce the cost at stations that require less machining time. However, optimization techniques available through the literature do not effectively utilize the idle time for the different stations generated during the balancing of the system. Proposed in this paper is an optimization method which utilizes the idle time to the full extent at all machining stations, with the intention of improving tool life and thus achieving cost reduction. The mathematical analysis considers the optimization of the production cost with an equality constraint of zero idle time for the stations with idle time. Physical constraints regarding the cutting parameters, force, power, surface finish, etc., as they arise in different operations, are also considered. The aforementioned problem has been theoretically analyzed and a computational algorithm developed. The advantages and effectiveness of the proposed approach are finally established through an example.

scholarly journals THE CHARACTERISTICS OPERATIONAL COST OF FREIGHT TRANSPORT IN SOUTH SULAWESI PROVINCE - INDONESIA

SINERGI ◽  
2020 ◽  
Vol 25 (1) ◽  
pp. 81
Author(s):  
Hakzah Hakzah ◽  
Muhammad Isran Ramli ◽  
Andi Irmayani Pawelloi
Keyword(s):  
Travel Time ◽  
Operating Cost ◽  
Freight Transportation ◽  
Freight Transport ◽  
Infrastructure Development ◽  
Time Model ◽  
South Sulawesi ◽  
Cost Modelling ◽  
Relationship Model ◽  
The Cost

Infrastructure development of the freight transport system has a vital position in accelerating Indonesian economic growth. This study aims to analyze one of the dominant characteristics of freight transportation, namely freight transportation costs in South Sulawesi Province. A questionnaire-based interview survey of operators was conducted to determine operator characteristics, vehicle characteristics, trip characteristics, and commodity characteristics. They are analyzing data using a descriptive statistical approach, building a cost and distance relationship model using a regression model approach while analyzing the priority of freight transport selection using an Analytical Hierarchy Process (AHP). An AHP is a decision-making model with multiple criteria. The analysis shows that the high costs are the component costs of the operator’s salary, fuel costs, and vehicle maintenance costs. Operating cost modelling provides a good level of models, both in terms of modes and commodities transported. In contrast, the travel time model based on modes and types of commodities shows inefficient. Based on the results, the pickup mode is optimal in cost and travel time with a weight of 39.8% and 50.3%. Trucks 3-4-5 Axles are the optimal mode of transportation when viewed in terms of distance (58.8%) and transportation volume (65.5%). In contrast, the two Axles Truck has characteristics between Pickups and 3-4-5 Axles Trucks. This result is better developed for a more comprehensive model of the cost of freight transport in South Sulawesi Province, Indonesia. 

Cost and Productivity Impacts of a “Smart” Paratransit System

1997 ◽  
Vol 1571 (1) ◽  
pp. 81-87 ◽  
Author(s):  
T. Chira-Chavala ◽  
Christoffel Venter
Keyword(s):  
Data Base ◽  
Travel Time ◽  
Ride Comfort ◽  
Operating Cost ◽  
Efficient Manner ◽  
Scheduling System ◽  
Transit Agencies ◽  
The Cost ◽  
New System

The cost and productivity impacts of an advanced paratransit system are analyzed; the system uses a digital geographical data base and an automated trip scheduling system to automate vehicle and passenger scheduling functions. The results indicate that such a system enables transit agencies to accommodate rapid increases in the paratransit demand in an efficient manner, which could not be accomplished by a manual or semimanual scheduling system. For the case study presented, this new system resulted in 13 percent savings in unit transportation operating cost and a significant increase in the percentage of shared rides. These benefits were achieved without affecting passengers’ travel time or ride comfort.

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.

An economic evaluation of a telehealth network in British Columbia

2007 ◽  
Vol 13 (5) ◽  
pp. 251-256 ◽  
Author(s):  
Joseph Schaafsma ◽  
Stefan V Pantazi ◽  
Jochen R Moehr ◽  
Christine R Anglin ◽  
Nicole A Grimm
Keyword(s):  
British Columbia ◽  
Economic Evaluation ◽  
Travel Time ◽  
Opportunity Cost ◽  
Operating Cost ◽  
Cost Effective ◽  
Health Care Facilities ◽  
Travel Costs ◽  
Utilization Data ◽  
The Cost

We carried out an economic evaluation of the northernmost five sites of the British Columbia telehealth network. The videoconferencing network links health-care facilities in 12 communities with Vancouver, for clinical consultations, administrative meetings and educational sessions. The economic evaluation was based on the netcost criterion (i.e. cost of telehealth minus travel costs avoided). Cost and utilization data were obtained from client interviews and log data compiled between September 2001 and January 2003. The results showed that the subnetwork of five sites was not only cost reducing, but also cost-effective. Travel costs for administrative meetings were reduced by $724,457/annum and were greater than the annual fixed and variable costs of all the telehealth sessions ($553,740). A sensitivity analysis was conducted on six parameters: amortization period, opportunity cost of capital, operating cost of a telehealth session (by type of session), number of telehealth sessions, travel time and the opportunity cost of travel time. The study suggests that the cost-effectiveness of telehealth to remote areas will increase over time as the cost of equipment continues to fall, as network connections become cheaper and as utilization rates rise.

scholarly journals Research on Route Deviation Transit Operation Scheduling—A Case Study in Suburb No. 5 Road of Harbin

2022 ◽  
Vol 14 (2) ◽  
pp. 633
Author(s):  
Xianglong Sun ◽  
Sai Liu
Keyword(s):  
Travel Demand ◽  
Search Algorithm ◽  
Operating Cost ◽  
Heuristic Search Algorithm ◽  
Scheduling Model ◽  
Special Groups ◽  
Passenger Travel ◽  
Response Modes ◽  
Transit Operation ◽  
Operation Scheduling

Route deviation transit is a flexible “door-to-door” service method that combines the efficiency of conventional public transport modes and the flexibility of demand response modes, meeting the travel needs of people with low travel density and special groups. In this paper, the minimum value of the sum of vehicle operating cost and passenger travel cost was the optimal goal, and the RDT multi-vehicle operation scheduling model was constructed. Taking the available relaxation time as the control parameter of the RDT system and considering the insertion process of the random travel demand of the passengers during the operation process, we used a heuristic search algorithm to solve the scheduling model. This paper took Suburb No. 5 Road of Harbin as an example, using MATLAB to simulate the RDT operation scheduling model to verify the stability and feasibility of the RDT system under different demands. The results showed that under different demand conditions, the system indicators such as passenger travel time, waiting time, and vehicle mileage in the RDT system fluctuated very little, and the system performance was relatively stable. Under the same demand conditions, the per capita cost of the RDT system was 5.9% to 10.8% less than that of the conventional bus system. When the demand ρ is 20~40 person/hour, the RDT system is more effective than the conventional bus for the 5 bus in the suburbs of Harbin.

scholarly journals A HYBRID OPTIMIZATION METHOD FOR VEHICLE ROUTING PROBLEM USING ARTIFICIAL BEE COLONY AND GENETIC ALGORITHM

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 293-297 ◽  
Author(s):  
M. Davoodi ◽  
M. Malekpour Golsefidi ◽  
M. S. Mesgari
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Artificial Bee Colony ◽  
Optimization Method ◽  
Geospatial Information ◽  
Routing Problem ◽  
Bee Colony ◽  
The Cost ◽  
Nearest Neighborhood

Abstract. Vehicle Routing Problem is one of the classic problems in GIS (Geospatial Information System) which had been studied for long times. An answer can be accepted as a good solution if it would be able to optimize the total length of the route or decrease the number of vehicles. A VRP defines finding the optimum route for some vehicles that serve to some customers and return to the service center. This problem is economically important because the cost and the time of serving to costumers are related to optimization of the problem’s answer. Furthermore, there are many problems like BUS management, Post pickup and delivery system and other servicing systems, which are technically similar to VRP. The aim of these problems is finding a composition of optimum routes between server and costumers. In addition, as the cost is related to time, finding shortest path means decreasing cost serving and decreasing time. In this article, a hybrid model using Artificial Bee Colony and Genetic Algorithm is proposed to solve VRP. In the first step, Artificial Bee Colony has been used to find a solution for five vehicles. The scout and the onlooker bees produced in 8 modes by two methods including the nearest neighborhood and the wide neighborhood. In the second step, the Genetic Algorithm helps to optimize the solutions. The results show that the production of the scout bees is the most effective factor in the answers to the problem and helps greatly converging the answers as soon as possible.

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

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