A Bi-objective Model of Many-To-Many Hub Vehicle Location-Routing Problem by Considering Hard Time Window and Vehicle-Cost Balancing
Enhancing the efficacy and productivity of transportation system has been on the most common issues in recent decades, noteworthy to the industrial managers and expert so that the products are delivered to the clients at right time and the least costs. Therefore, there are two important issues; one is to create hub as the as intermediaries for streaming from multiple origins to multiple destinations and also responding to the tours of every hub at the proper time. The other is a route where the vehicles should pay at time window of each destination node. On the other hand, these problems may cause cost differences between hub and interruption of their balance. Accordingly, this paper presents a model dealing with cost balancing among the vehicles as well as reducing the total cost of the system. Given the multi-objective and NP-Hard nature of the issue, a multi-objective imperialist competitive algorithm (MOICA) is suggested to provide Pareto solutions. The provided solutions are at small, average and large scales are compared with the solutions provided by Non-Dominated Sorting Genetic Algorithm (NSGA-II) algorithm. Then, its performance is determined using the index for evaluating the algorithm performance efficacy to solve the problem at large dimensions.</span></span></span></span></span></span>
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A New Multi-Objective Location Routing Problem with Hybrid Fuzzy-Stochastic Approach by Considering Capacity Restrictions: Model, Solution and Application
Amir-Mohammad Golmohammadi *, , Fazel Hajizadeh Ebrahimi
International Journal of Supply and Operations Management, Spring 2025 -
A Simulation-Based Approach for Designing an Innovative Double Sampling Plan for Two Stages Process
Amir-Mohammad Golmohammadi *, Ali Shahabi, , Fazel Hajizadeh Ebrahimi
Journal of Advances in Industrial Engineering, Summer and Autumn 2024