Related Experiment Video
Updated: Sep 23, 2025
09:04
A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
Published on: June 1, 2022
3.2K
Modeling a periodic electric vehicle-routing problem considering delivery due date and mixed charging rates using
Maryam Elahi1, Soroush Avakh Darestani2,3
1Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran.
Summary
This study presents a mathematical model to minimize electric vehicle (EV) travel and recharging costs. The simulated annealing algorithm efficiently solves this optimization problem, offering a viable solution for sustainable transportation.
Area of Science:
- Sustainable Transportation
- Operations Research
- Environmental Science
Background:
- Rising fossil fuel costs and environmental concerns drive demand for alternative transportation.
- Electric vehicles (EVs) are a key solution for reducing atmospheric pollution from conventional vehicles.
- Optimization of EV logistics, including travel and charging, is crucial for widespread adoption.
Purpose of the Study:
- To develop a mathematical model for minimizing the total travel distance and recharging expenses of electric vehicles (EVs) over a specified period.
- To solve the developed optimization model using the simulated annealing (SA) algorithm.
- To evaluate the efficiency and solution quality of the SA algorithm compared to traditional methods.
Main Methods:
- Formulation of a mathematical optimization model to minimize combined EV travel and recharging costs.
- Implementation of the simulated annealing (SA) algorithm to solve the optimization problem.
- Comparative analysis of SA algorithm performance against GAMS for 30 diverse test cases.
Main Results:
- The simulated annealing (SA) algorithm demonstrated good efficiency in terms of processing time and solution quality for EV logistics optimization.
- Processing time for the SA algorithm increased gradually with problem complexity.
- GAMS exhibited a significantly steeper increase in processing time as problem complexity grew.
Conclusions:
- The simulated annealing (SA) algorithm is an effective metaheuristic for optimizing electric vehicle (EV) operational costs.
- SA offers a computationally efficient approach for minimizing travel distance and recharging expenses in EV fleets.
- The proposed model and algorithm provide a valuable tool for enhancing the economic viability of electric transportation.
Keywords:
Delivery due dateElectric vehicle (EV)Green routingMathematical programmingSimulated annealing (SA)More Related Videos
Related Concept Videos
01:21Distributed Loads: Problem Solving
747
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
747
01:26The Power Flow Problem and Solution
353
Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk, phase angle δk, real power Pk, and reactive power Qk. Two of these four variables are inputs, while the...
353
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
107
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
107
01:24Fast Decoupled and DC Powerflow
305
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
305
01:17Ampere-Maxwell's Law: Problem-Solving
783
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
783
01:23Maximum Power Flow and Line Loadability
190
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
190