Article
Computer Science, Information Systems
Liting Wang, Chao Song, Yu Sun, Cuihua Lu, Qinghua Chen
Summary: The vehicle routing problem (VRP) is a common problem in logistics and transportation. With the development of neural network technology, solving VRP through neural combinatorial optimization has gained increasing attention. This study proposes a multi-objective vehicle routing optimization algorithm based on preference adjustment, which utilizes deep reinforcement learning to adaptively search for better combinations of preferences, resulting in improved results compared to existing models.
Article
Computer Science, Artificial Intelligence
Chao Wang, Biao Ma, Jiye Sun
Summary: This paper proposes a co-evolutionary genetic algorithm with knowledge transfer to solve the CVRP problem with workload balancing. Experimental results show that the algorithm has faster convergence speed and superior convergence.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Bin Cao, Weizheng Zhang, Xuesong Wang, Jianwei Zhao, Yu Gu, Yan Zhang
Summary: In order to address the growing problem of traffic pollution caused by the rapid increase in motor vehicles, a many-objective optimization model of multi-depot heterogeneous vehicle CARP is constructed in this study. Through the use of a memetic algorithm based on Two_Arch2, the model is effectively optimized and the pollution problem is successfully solved.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Article
Engineering, Multidisciplinary
Ibrahim Demir, Berna Kiraz, Fatma Corut Ergin
Summary: In this study, two meta-heuristic approaches based on NSGA-II and AMOSA were proposed to solve the multi-objective capacitated multiple allocation hub location problem (MOCMAHLP). Experimental analysis and fine-tuning tests revealed that NSGA-II performs better for larger networks, while AMOSA performs better for smaller networks.
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH
(2022)
Article
Computer Science, Artificial Intelligence
Mazhar Ansari Ardeh, Yi Mei, Mengjie Zhang, Xin Yao
Summary: The uncertain capacitated arc routing problem (UCARP) is a difficult combinatorial optimization problem in logistics. Genetic programming (GP) hyper-heuristic has been successfully applied to evolve routing policies for this problem. However, existing methods are not sufficient in handling the change from one instance to another. To address this issue, we propose a novel knowledge transfer GP with an auxiliary population. Experimental results show that our method outperforms the state-of-the-art GP approaches in terms of both final performance and convergence speed.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2023)
Article
Mathematics
Zsuzsanna Nagy, Agnes Werner-Stark, Tibor Dulai
Summary: In this study, an ABC algorithm for the CARP problem was developed and proved to excel in finding high-quality solutions and being efficient. The sub-route plan operator was also shown to be more effective in finding better solutions compared to other operators.
Article
Computer Science, Information Systems
Wei Yu, Yujie Liao, Yichen Yang
Summary: In this work, the Multi-depot Capacitated Arc Routing Problem (MCARP), a generalization of the classical capacitated arc routing problem, is investigated. Exact and approximation algorithms are developed for different variants of the MCARP. The effectiveness of the algorithms for the multi-depot rural postman problem is demonstrated through extensive numerical experiments.
TSINGHUA SCIENCE AND TECHNOLOGY
(2023)
Article
Operations Research & Management Science
Erfan Babaee Tirkolaee, Alireza Goli, Selma Gutmen, Gerhard-Wilhelm Weber, Katarzyna Szwedzka
Summary: This study develops a mixed-integer linear programming model to address the sustainability issue in municipal solid waste management. By minimizing costs and environmental emissions, maximizing citizen satisfaction, and reducing workload deviation, the efficiency of problem solving is improved.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Shaolin Wang, Yi Mei, Mengjie Zhang, Xin Yao
Summary: This article proposes a novel genetic programming approach to solve the uncertain capacitated arc routing problem. By simplifying routing policies using a niching technique and storing the simplified policies in an external archive, the evolved routing policies are more effective and simpler.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2022)
Article
Computer Science, Artificial Intelligence
Hao Tong, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao
Summary: This article proposes a novel framework to solve the dynamic CARP problem, which can benefit from existing static CARP algorithms and significantly improve the performance of dynamic optimization algorithms.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2022)
Article
Operations Research & Management Science
Maliheh Khorsi, Seyed Kamal Chaharsooghi, Ali Husseinzadeh Kashan, Ali Bozorgi-Amiri
Summary: Vehicle routing models play a crucial role in disaster response by optimizing the allocation of relief resources to minimize negative consequences. This paper proposes a multi-period, multi-depot, multi-trip vehicle routing problem and solves it using a grouping metaheuristic algorithm. The performance of the solution method is evaluated through various test problems and statistical comparisons, and sensitivity analyses are conducted to validate the model.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Chahid Ahabchane, Andre Langevin, Martin Trepanier
Summary: This paper studies the Mixed Capacitated General Routing Problem (MCGRP) under demand uncertainty and service hierarchy using a robust optimization approach, presented corresponding formulations and models, and conducted computational analysis including Monte Carlo simulations.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Long Chen, Peng Xu, Reginald R. Souleyrette
Summary: This article introduces a Rich Arc Routing Problem (RARP) with specific constraints, such as time limits and non-overlapping paths. An Improved LIP-ASD (I-LIP-ASD) algorithm is proposed to tackle the challenge, which generates initial populations by combining existing individuals and outputs all nondominated solutions in each decomposed sub-space. The effectiveness of the proposed solution algorithm is evaluated and demonstrated through experiments over converted capacitated arc routing problem instances and a real-world case.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Joao Janela, Maria Candida Mourao, Leonor Santiago Pinto
Summary: This study focuses on the household waste collection problem in Seixal, Portugal, and proposes a new methodology by modeling it as a mixed capacitated arc routing problem. The proposed methodology uses a geographic information system for input/output and reducing problem dimensions, and employs a matheuristic to iteratively solve a new hybrid model and generate feasible trips. The quality of the solutions is evaluated using total time and attractiveness measures, including a new measure called weighted hull overlap. Computational results show that the proposed methodology performs well.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Computer Science, Information Systems
Xiaoshu Xiang, Ye Tian, Ran Cheng, Xingyi Zhang, Shengxiang Yang, Yaochu Jin
Summary: This study proposes a benchmark generator for online dynamic single-objective and multi-objective optimization problems. It adjusts the influence of solutions found in each environment on the problems in the next environment through different types of functions and predefined parameters, and suggests a test suite consisting of continuous and discrete online dynamic optimization problems. The proposed OL-DOP test suite exhibits time-deception compared to existing benchmark test suites and evaluates the ability of dynamic optimization algorithms to tackle the influence of solutions on successive environment problems.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Vladimir Simic, Branko Milovanovic, Strahinja Pantelic, Dragan Pamucar, Erfan Babaee Tirkolaee
Summary: Accidents in petroleum transportation have severe consequences for the population and environment. This study addresses the sustainable route selection problem using a multi-criteria decision-making approach. Practical and methodological evaluation frameworks were introduced to help authorities find the most sustainable route, and an advanced decision-making tool based on the ITARA and EDAS methods under the T2NN environment was developed. The research provides guidelines for selecting sustainable transportation routes and offers a model that can be applied to solve other complex MCDM problems.
INFORMATION SCIENCES
(2023)
Review
Green & Sustainable Science & Technology
Iman Shahsavani, Alireza Goli
Summary: The circular economy and circular supply chain are environmentally friendly alternatives that aim to reduce energy consumption, but there are limited studies on the design of circular supply chain networks.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Management
Selcuk Korucuk, Erfan Babaee Tirkolaee, Ahmet Aytekin, Darjan Karabasevic, Caglar Karamasa
Summary: In the context of the expanding competition and differentiation in the sector of Supply Chain Management, Agile Supply Chain Management (ASCM) and Industry 4.0 practices have become crucial for companies to ensure survival and provide flexibility. This study examines the critical success factors of ASCM and identifies the appropriate risk reduction strategy for companies in the rubber and plastic products industry in Istanbul. The use of Bipolar Neutrosophic Stepwise Weight Assessment Ratio Analysis (BN-SWARA) and Bipolar Neutrosophic Technique for Order of Preference by Similarity to Ideal Solution (BN-TOPSIS) methods helps in ranking and discussing the results, providing managerial insights and decision aids.
OPERATIONS MANAGEMENT RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Vladimir Simic, Svetlana Dabic-Miletic, Erfan Babaee Tirkolaee, Zeljko Stevic, Muhammet Deveci, Tapan Senapati
Summary: Management of end-of-life tires (ELTs) has become an important sustainability requirement that follows circular economy principles. Finding environmentally friendly and cost-effective solutions for ELT management is important, especially for large freight transportation companies. This study introduces an evaluation framework and decision support model to assist transportation companies in managing ELT flows and reveals the most sustainable strategy.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Vladimir Simic, Svetlana Dabic-Miletic, Erfan Babaee Tirkolaee, Zeljko Stevic, Ali Ala, Arash Amirteimoori
Summary: This research aims to introduce a neutrosophic multi-criteria group decision-making tool that supports the transition and upgrading of WMS with Industry 4.0-based solutions. The advanced two-stage model is based on the LOPCOW method and the ARAS method under the T2NN environment. The research findings show that AGVs are the most favorable Industry 4.0-based material handling solution.
APPLIED SOFT COMPUTING
(2023)
Article
Operations Research & Management Science
Alireza Goli, Erfan Babaee Tirkolaee, Amir-Mohammad Golmohammadi, Zumbul Atan, Gerhard-Wilhelm Weber, Sadia Samar Ali
Summary: Supply chain network design is vital in today's competitive environment, especially considering the increasing transportation costs for manufacturing companies. This research proposes a flexible, sustainable, multi-product, multi-period, and IoT-based supply chain network with integrated forward/reverse logistics system. The network involves various actors, such as suppliers, producers, distribution centers, customers, repair/disassembly centers, recycling centers, and disposal centers. An IoT system is utilized for direct shipping, allowing the management of both direct and indirect delivery. A Multi-Objective Mixed-Integer Linear Programming model is used to incorporate options and considerations, which is then transformed into a single-objective model using Goal Programming. To handle demand uncertainty, a robust optimization approach is applied. Numerical results demonstrate that the proposed model effectively optimizes the supply chain network, with the robustness dependent on uncertainty budgets and observed up to a 213.528% increase in the GP objective function.
CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Alireza Goli, Erfan Babaee Tirkolaee
Summary: Product portfolio design plays a crucial role in the financial and physical flows of supply chains, especially for dairy products. This study proposes a closed-loop supply chain network for dairy products to maximize net cash flow and shareholder payments. The accelerated Benders decomposition algorithm and three multi-objective optimization methods are used to address the complexity and bi-objectiveness of the model, respectively. A real case study in Iran shows significant improvements in net cash flow and shareholder payments compared to the current situation, while reducing CPU time by 10.8%.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Mostafa Ekhtiari, Mostafa Zandieh, Erfan Babaee Tirkolaee
Summary: This study focuses on the problem of dam site selection and proposes a new model based on NCP and stochastic programming for handling uncertainty. By using the IGDEMATEL method to determine criterion weights and evaluating the results through simulation, similar outcomes to the simulation model were obtained. This research contributes to addressing the issue of dam site selection in water resources management.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
Omer Faruk Gorcun, Ahmet Aytekin, Selcuk Korucuk, Erfan Babaee Tirkolaee
Summary: Health institutes need to develop partnerships with logistics service providers to solve the problem of healthcare waste disposal.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
Xiaoli Feng, Alireza Goli
Summary: This research examines the profound impact of circular economy practices on financial performance and reveals the intricate relationship between the two through a proposed mathematical model. The study finds that circular economy practices significantly influence financial performance, accounting for 15.7% of its variance. The combined synergy of circular economy practices and financial performance contributes to a noteworthy 24.8% variance in overall company performance.
Editorial Material
Green & Sustainable Science & Technology
Gerhard-Wilhelm Weber, Alireza Goli, Erfan Babaee Tirkolaee
Editorial Material
Green & Sustainable Science & Technology
Erfan Babaee Tirkolaee, Alireza Goli, Heris Golpira, Ernesto D. R. Santibanez Gonzalez
Article
Business
Hana Tomaskova, Erfan Babaee Tirkolaee, Rakesh Dulichand Raut
Summary: Managers play a critical role in decision-making by considering their organization's needs, goals, and objectives. It is important for them to have prior knowledge to correctly apply written material produced before or after the issue it addresses. Our study demonstrates that fundamental business process analysis and reengineering can improve decision-making processes by assessing and redesigning procedures. By using this approach, managers can ensure their organization's objectives are met while enhancing efficiency and productivity.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Engineering, Industrial
Peiman Ghasemi, Fariba Goodarzian, Vladimir Simic, Erfan Babaee Tirkolaee
Summary: This study presents a new mathematical model for a Plasma Supply Chain Network (PSCN) that aims to maximize blood donor coverage and minimize various costs in the network. The model considers both resiliency and efficiency during the COVID-19 outbreak and incorporates stochastic chance-constrained programming to handle uncertain parameters. Solution techniques include the ε-constraint method for small- and medium-sized problems and the multi-objective invasive weed optimization algorithm for large-sized problems. The proposed methodology is validated through problem instances and assessment metrics, and a real case study and sensitivity analyses are conducted to configure the optimal network.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS
(2023)
Review
Computer Science, Information Systems
Ali Ebadi Torkayesh, Erfan Babaee Tirkolaee, Aram Bahrini, Dragan Pamucar, Amir Khakbaz
Summary: Multiple Criteria Decision-Making (MCDM) is a reliable and applicable decision-making tool for addressing complex and multi-dimensional problems in line with sustainable development and circular economy concepts. However, there is a research gap in literature review regarding the use of Multi-Attributive Border Approximation area Comparison (MABAC) as an intelligent decision-making system. This study aims to fill this gap by presenting a comprehensive literature review of 117 articles on MABAC's recent developments and applications, as well as providing future outlook on challenges and trends.