The Vehicles Traffic Flow Optimization in an Urban Transportation System by Using Simulation Modeling

Coman, Marian; Badea, Dorel

doi:10.1515/raft-2017-0026

Cited by 3 publications

(1 citation statement)

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“…Study [26] presented a two-stage optimization of intermodal terminals' main parameters via AnyLogic software combining the agent-based system dynamics simulation with the agent-based discrete-event simulation models to improve the decision-making process in selection of the terminals' strategic planning. Paper [27] described an AnyLogic-optimized vehicles' flow in a crowded urban area to obtain a travel time reduction for all road users. With the AnyLogic procedures, authors [28] developed and improved a "leagile" supply chain operation by shortening the supply chain length, accelerating the market demand response and personalizing the customers' needs.…”

Section: Problem Statementmentioning

confidence: 99%

Freight Fleet Management Problem: Evaluation of a Truck Utilization Rate Based on Agent Modeling

Samchuk¹,

Копытков²,

Rossolov³

2022

Komunikácie

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The article deals with the problem of estimating the rational number and utilization rate of the vehicles' fleet. According to the analysis results of the state-of-the-art literature it has been revealed that the issue of substantiating the rational fleet size and the rate of its utilization were not fully solved. The purpose of the study was to increase the efficiency of servicing transportation orders by determining the required number of vehicles. The goal of the research was the influence of the transportation process parameters on the truck utilization rate. Originating from the probabilistic nature of the transportation process, it has been proposed to use the AnyLogic software product to develop a simulation model for vehicle orders' servicing. From the processing of the experimental results by the regression analysis methods, it has been found that the dependence of changes in the vehicle utilization rate is of a linear form.

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Section: Problem Statementmentioning

confidence: 99%

Freight Fleet Management Problem: Evaluation of a Truck Utilization Rate Based on Agent Modeling

Samchuk¹,

Копытков²,

Rossolov³

2022

Komunikácie

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Optimizing Algerian Company’s Delivery Fleet with Agent_Based Model in Anylogic

Bounadi,

Boussalia,

Bellaouar

2023

Transport and Telecommunication Journal

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The utilization of simulation modelling in supply chain management has proven to be a valuable tool for logistics service providers, enabling them to optimize their operations and meet customer demands efficiently. AnyLogic, with its diverse capabilities in discrete event simulation, system dynamics, and agent-based simulation, stands out as a powerful software solution for tackling complex supply chain challenges. This paper significantly contributes by demonstrating the practical implementation of AnyLogic in the modelling and simulation of agro-food product distribution network, particularly vegetable oils from the Cevital group. Additionally, the study integrates an optimization experiment to ascertain the optimal number of vehicles required to meet a specific customer demand while ensuring a high level of fleet utilization. The obtained results are very encouraging and demonstrate the feasibility and effectiveness of our approach.

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Information Technology of Decision Support to Design the Transportation Orders' Servicing

Davidich

Samchuk

Копытков

et al. 2021

MEC

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The main purpose of most transport companies is to provide the quality services to customers with minimal costs. At the same time, determination of the number of vehicles and their utilization rate when satisfying transportation orders is the important task, the proper solution of which leads to the full and timely servicing and contributes to an increase of a transport company's competitiveness in the present-day market. Due to the analysis results of the state-of-the-art literature and Internet sources, it has been revealed that the problem of finding the rational fleet size and the rate of its utilization to complete the transportation orders were not fully solved. From the criteria analysis it has been proposed to substantiate the vehicle fleet size according to the car utilization rate to be assigned as the "vehicle working time-to-total working time" ratio. Considering the probabilistic nature of the transportation process, a simulation model to complete the orders by a truck fleet has been developed in the AnyLogic environment. An experimental plan has been developed to reproduce the real transportation order conditions and consisted of 27 series, each of which was of 100 experiments. The variation range of input factors, which was the transportation distance, vehicles' number and orders' hourly intensity were [10;30], [1;3] and [0.6;1], respectively. From the experimental results processing by the regression analysis methods, it has been found that the dependence of changes in the car utilization rate, transportation distance, vehicle' number and orders' intensity was of linear form. The obtained dependence has been estimated via the determination coefficient, which was 0.95, and indicated the high quality of the model proposed. The resulting model allows calculating the required number of vehicles from their operating conditions. In the case study the 2 vehicles were recommended to service the transportation orders. Further research efforts can be taking into account a larger number of influencing factors, increasing their variation range and obtaining dependencies to describe the presented criterion change to acceptable accuracy.

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The Vehicles Traffic Flow Optimization in an Urban Transportation System by Using Simulation Modeling

Abstract: ABSTRACT

Cited by 3 publications

References 1 publication

Freight Fleet Management Problem: Evaluation of a Truck Utilization Rate Based on Agent Modeling

Freight Fleet Management Problem: Evaluation of a Truck Utilization Rate Based on Agent Modeling

Optimizing Algerian Company’s Delivery Fleet with Agent_Based Model in Anylogic

Information Technology of Decision Support to Design the Transportation Orders' Servicing

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