Article
Computer Science, Artificial Intelligence
Samuel Nucamendi-Guillen, Alejandra Gomez Padilla, Elias Olivares-Benitez, J. Marcos Moreno-Vega
Summary: This paper introduces the multi-depot open location routing problem (MD-OLRP) and proposes an intelligent metaheuristic to solve it, achieving high-quality solutions and saving the company 30.86% in costs.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Economics
Sercan Donmez, Cagri Koc, Fulya Altiparmak
Summary: In this study, we introduce the Mixed Fleet Vehicle Routing Problem with Time Windows and Partial Recharging by Multiple Chargers (MF-VRP-MC), and propose a mixed integer mathematical programming model and an Adaptive Large Neighborhood Search (ALNS) algorithm. The computational results demonstrate that our ALNS algorithm performs well on large-scale instances.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Computer Science, Artificial Intelligence
Vincent F. Yu, Panca Jodiawan, Aldy Gunawan
Summary: This study addresses the Green Mixed Fleet Vehicle Routing Problem with Realistic Energy Consumption and Partial Recharges by developing an adaptive Large Neighborhood Search heuristic. Experimental results show that the proposed algorithm finds optimal solutions for most small-scale instances in a significantly faster computational time compared to CPLEX solver and obtains high quality solutions for medium- and large-scale instances. Numeric studies are also conducted to analyze the potential carbon emission reduction from the proposed model.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
Vinicius R. Maximo, Jean-Francois Cordeau, Maria C. V. Nascimento
Summary: In this paper, an Adaptive Iterated Local Search (AILS) heuristic is proposed for the Heterogeneous Fleet Vehicle Routing Problem (HFVRP). The results of computational experiments indicate that AILS outperformed state-of-the-art metaheuristics on 87% of the instances.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Paolo Fadda, Simona Mancini, Patrizia Serra, Gianfranco Fancello
Summary: In the field of international maritime transport, the phenomenon of naval gigantism has emerged with the advent of ever larger ships. These giant vessels face operational issues due to their large draft, such as restrictions in accessing small ports and determining the optimal sequence of port visits. Additionally, draft restrictions also impact the fleet sizing problem, although large ships offer lower travel costs per load unit due to economies of scale.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Computer Science, Information Systems
Vincent F. Yu, Hadi Susanto, Panca Jodiawan, Tsai-Wei Ho, Shih-Wei Lin, Yu-Tsung Huang
Summary: With the growth of e-commerce, city logistics need to address the increasing complexity of last-mile delivery due to rising customer demands. Using parcel lockers as an alternative delivery option can alleviate this problem and save costs. This research introduces a new variant of the vehicle routing problem that includes locker delivery as an option, aiming to minimize total traveling costs.
Article
Computer Science, Interdisciplinary Applications
Xin Wang, Yijing Liang, Xiaoyang Wei, Ek Peng Chew
Summary: Seaports are crucial for connecting inland and maritime transportation, and tugboats play a vital role in providing enough power and ensuring safety for container ships when entering and leaving seaports. Thus, scheduling tugboats in seaport management is essential to facilitate the cost-effective movement of container ships. This paper investigates the tugboat scheduling problem considering multiple services at multiple waypoints to optimize the utilization of limited tugboats. An efficient adaptive large neighborhood search algorithm with a feasibility check procedure is proposed and validated through computational experiments, providing valuable managerial insights based on sensitivity analysis.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Sinaide Nunes Bezerra, Marcone Jamilson Freitas, Sergio Ricardo de Souza
Summary: This article addresses the MDVRPTW* problem and proposes an algorithm called SGVNSALS to solve it. The algorithm outperforms other algorithms in terms of the number of used vehicles and covered distance.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Engineering, Civil
Selin Hulagu, Hilmi Berk Celikoglu
Summary: This study focuses on solving the complex problem of staff service bus route planning for a university in a metropolitan city. It considers the environmental concerns and provides exact solutions for both homogeneous and heterogeneous vehicle fleets. The results show a significant reduction in cost for the heterogeneous fleet, as well as an optimal routing plan that maximizes the utilization of all assigned buses.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Energy & Fuels
Roger Ksiazek, Katarzyna Gdowska, Antoni Korcyl
Summary: This paper discusses the optimization problem of using electric garbage trucks for solid waste collection and develops an MIP program to generate optimal crew schedules for heterogeneous fleet. It studies the impact of electric vehicles on crew rostering and the challenges in route planning.
Article
Computer Science, Interdisciplinary Applications
Nima Moradi, Ihsan Sadati, Buelent Catay
Summary: This paper presents a study on the application of Autonomous Delivery Vehicles (ADVs) in last-mile delivery for urban logistics. The authors propose a two-phase metaheuristic approach to solve the routing problem using multi-stop ADVs. Computational experiments show that the proposed approach can generate high-quality solutions with minimal computational effort, outperforming an exact solver in most instances.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Hatice Calik, Ammar Oulamara, Caroline Prodhon, Said Salhi
Summary: This paper focuses on finding the optimal locations of recharging stations and routing electric vehicles in a goods distribution system. A novel mathematical formulation and an efficient Benders decomposition algorithm are proposed to minimize total costs. The study provides insights for both management and methodology in solving environmental logistics problems efficiently.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Operations Research & Management Science
Munise Kubra Sahin, Hande Yamana
Summary: The multi-trip vehicle routing problem (MTVRP) extends the classic VRP by allowing vehicles to make multiple trips in a workday, catering to the needs of city logistics where smaller and cleaner vehicles are gaining importance. This problem involves a heterogeneous fleet, multiple depots, and different travel times for small and large vehicles, and can be solved effectively by a new heuristic algorithm based on reduction in graph size. Computational experiments demonstrate that the proposed algorithm is efficient in solving instances with multiple customers, depots, and vehicle types.
TRANSPORTATION SCIENCE
(2022)
Article
Mathematics
Vincent F. Yu, Winarno, Achmad Maulidin, A. A. N. Perwira Redi, Shih-Wei Lin, Chao-Lung Yang
Summary: This research introduces a variant of the vehicle routing problem and successfully solves it using a simulated annealing heuristic algorithm. The motivation behind the research is to help companies reduce operational costs and provide a practical strategy.
Article
Computer Science, Interdisciplinary Applications
Timo Hintsch
Summary: The paper introduces a large multiple neighborhood search algorithm for the SoftCluVRP, utilizing various cluster destroy and repair operators and two post optimization components. Computational experiments demonstrate that the algorithm outperforms existing heuristic approaches and provides 130 new best solutions for medium-sized instances.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Management
Yu-Chung Tsao, Felix Arril Simbara Barus, Chien-Wei Ho
Summary: This research examines the impacts and acceptance of fifth-generation technology by combining the unified theory of acceptance and use of technology with the triple bottom line. Through analyzing data sets from Taiwanese manufacturing and healthcare organizations, the findings show that user attitudes and beliefs regarding fifth-generation technology have an impact on sustainability.
INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS
(2022)
Article
Engineering, Industrial
Yu-Chung Tsao, Pei-Ling Lee
Summary: This paper examines the issue of credit risk in a decentralised supplier-retailer channel and proposes a composite contract for channel coordination, which includes cost-sharing of informational effort and credit risk.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS
(2023)
Article
Thermodynamics
Yu-Chung Tsao, Vu-Thuy Linh
Summary: This study examines a pricing scheme problem between a power company and an electricity consumer using a nonlinear approach. The results indicate that considering the regret value increases the electricity price, and the case with peer-to-peer trading is more beneficial for the prosumer.
Article
Information Science & Library Science
Che-Yuan Chang, Yi-Ying Chang, Yu-Chung Tsao, Sascha Kraus
Summary: This study examines the relationship between top management team bricolage and performance, and the mediating role of unit ambidexterity. The study also explores the moderating effects of potential absorptive capacity and realized absorptive capacity. The findings highlight the importance of absorptive capacity in understanding how TMT bricolage influences unit ambidexterity and performance.
JOURNAL OF KNOWLEDGE MANAGEMENT
(2022)
Article
Computer Science, Artificial Intelligence
Yu-Chung Tsao, Magda Delicia, Thuy-Linh Vu
Summary: This study focuses on the marker planning problem in the apparel industry and proposes a particle swarm optimization-based heuristic approach to optimize the utilization efficiency of fabric. A pixel-based representation is used to handle the geometry of clothing patterns, and the performance of the approach is enhanced by combining with local search, genetic algorithm, and simulated annealing. Experimental results show that the proposed approach achieves competitive results with shorter fabric length and CPU time compared to traditional methods.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Interdisciplinary Applications
Yu-Chung Tsao, Tsehaye Dedimas Beyene, Vo-Van Thanh, Sisay G. Gebeyehu
Summary: This study considers the establishment of a power distribution network design with distributed renewable energy resources and the involvement of prosumers in the energy system. By developing a mathematical model and solution approach, the study determines the generation capacity of distributed renewable energy resources, differential prices, and buy-back price while maximizing the profit of a power plant. The results show that offering a high buy-back price to incentivize prosumers can lead to the highest profit.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Operations Research & Management Science
Yu-Chung Tsao, Thuy-Linh Vu
Summary: Operations and maintenance management for renewable energy projects plays a crucial role in improving the precision of energy system models. This study presents a profit model that integrates system reliability, predictive maintenance, and green insurance into electricity pricing and capacity problems. The results suggest that increased reliability of renewable energy systems leads to a decrease in insurance levels, but higher insurance levels result in reduced project investments.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Yu-Chung Tsao, Tsehaye Dedimas Beyene, Sisay G. Gebeyehu, Tsai-Chi Kuo
Summary: Community of prosumers in the energy market plays a significant role in enhancing the sustainability of power distribution networks. By generating energy for their consumption and selling surplus energy, prosumers contribute to the overall energy supply. This study analyzed the capacity of distributed renewable energy generation units, dynamic pricing mechanisms, and the impact on the net profit of the power company. The findings showed that the participation of prosumers and carbon trading increased the power company's net profit by 1.13%.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Operations Research & Management Science
Yu-Chung Tsao, Nandya Shafira Pramesti, Thuy-Linh Vu, Iwan Vanany
Summary: The development of technologies like the Internet of Things has transformed physical products into smart connected products (SCPs) that combine hardware, sensors, data storage, microprocessors, software, and connectivity. This study develops an inventory model that considers optimal pricing, production, and intelligent efforts for SCPs. The results show that considering the level of intelligent effort as a decision can greatly benefit the manufacturer, with a 55% increase in intelligent effort coefficient leading to a 65.8% increase in total profit.
RAIRO-OPERATIONS RESEARCH
(2023)
Article
Engineering, Industrial
Yu-Chung Tsao, Chien-Wei Ho, Chi-Chuan Wu
Summary: Unexpected crises, such as the COVID-19 pandemic, have significantly impacted businesses and supply chains globally, prompting many companies to adopt digitalization in order to adapt to the rapid changes. However, there is limited research on the mediating mechanism between digitalization and collaborative planning. This study, using structural equation modeling, examines how digital transformation improves collaborative planning through the mediation of management participation and information sharing. The results show that digital transformation has a significant impact on management and information sharing, and that management participation and information sharing have positive effects on collaborative planning. However, this study also reveals that digital transformation does not directly influence collaborative planning. Overall, this study contributes to the understanding of digitalization and manufacturing, and offers valuable suggestions for companies looking to develop digitalization and foster collaborative planning.
JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING
(2023)
Article
Construction & Building Technology
Yu-Chung Tsao, Thuy-Linh Vu
Summary: The increased smartness of buildings and technological advancements aim to reduce the impact of climate change by implementing renewable energy, efficient energy management, and greenhouse gas emission reduction. By using the internet of things, sensors, and data analysis, energy management can optimize energy usage and maintain a balance between energy supply and demand. However, it is crucial to accurately determine the optimal number and placement of sensors in a building for an efficient distributed sensor system.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Environmental Studies
Yen Hsun Chuang, Yu-Chung Tsao, Wei Yea Chen
Summary: The purpose of this study is to determine the optimal policy for fossil fuels and renewable energy allocation in Taiwan to decrease greenhouse gas emissions and maintain economic development until 2030. The results show that renewable energy rapidly increases to 5.8 billion kWh and natural gas increases to 54 million m(3) while maintaining energy consumption at the 2020 levels. Greenhouse gas emissions are expected to decrease to 20% of the 2005 levels by 2030. The Taiwanese government should consider the allocation of fossil fuels and renewable energy with linear growth in energy consumption to achieve carbon emission reduction goals.
ENERGY & ENVIRONMENT
(2023)
Article
Green & Sustainable Science & Technology
Yu-Chung Tsao, Thuy-Linh Vu
Summary: This paper proposes a two-stage approach to solving the optimal capacity, location, and allocation problems of energy storage systems in microgrids. In the first stage, a continuous approximation approach is used to formulate the long-term problems of storage system location, capacity, and renewable energy investment. In the second stage, the quantity dispatch problems are addressed to minimize operational costs. The results show that this approach can achieve cost minimization.
Article
Engineering, Industrial
Yu-Chung Tsao, Vu Thuy Linh, Tsung-Hui Chen
Summary: This study contributes to the field of supply chain management by investigating the impact of dual-channel supply chain competition and proposing a solution to channel conflicts, thus promoting the introduction of online channels.
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE
(2022)
Article
Engineering, Multidisciplinary
Yu-Chung Tsao, Hanifa-Astofa Fauziah, Thuy-Linh Vu, Nur-Aini Masrurohand
Summary: Trade credit financing is common in modern global economy, benefiting both sellers and buyers in business transactions. Sellers offer credit period to attract new buyers, while buyers accumulate revenue. The trade credit policies based on order quantity can provide varying degrees of delayed payment benefits for buyers.
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Rafael Praxedes, Teobaldo Bulhoes, Anand Subramanian, Eduardo Uchoa
Summary: The Vehicle Routing Problem with Simultaneous Pickup and Delivery is a classical optimization problem that aims to determine the least-cost routes while meeting pickup and delivery demands and vehicle capacity constraints. In this study, a unified algorithm is proposed to solve multiple variants of the problem, and extensive computational experiments are conducted to evaluate the algorithm's performance.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Ragheb Rahmaniani, Teodor Gabriel Crainic, Michel Gendreau, Walter Rei
Summary: Benders decomposition (BD) is a popular solution algorithm for stochastic integer programs. However, existing parallelization methods often suffer from inefficiencies. This paper proposes an asynchronous parallel BD method and demonstrates its effectiveness through numerical studies and performance enhancement strategies.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Giulia Caselli, Maxence Delorme, Manuel Iori, Carlo Alberto Magni
Summary: This study addresses a real-world scheduling problem and proposes four exact methods to solve it. The methods are evaluated through computational experiments on different types of instances and show competitive advantages on specific subsets. The study also demonstrates the generalizability of the algorithms to related scheduling problems with contiguity constraints.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Shaowen Yao, Chao Tang, Hao Zhang, Songhuan Wu, Lijun Wei, Qiang Liu
Summary: This paper examines the problem of two-dimensional irregular multiple-size bin packing and proposes a solution that utilizes an iteratively doubling binary search algorithm to find the optimal bin combination, and further optimizes the result through an overlap minimization approach.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Decheng Wang, Ruiyou Zhang, Bin Qiu, Wenpeng Chen, Xiaolan Xie
Summary: Consideration of driver-related constraints, such as mandatory work break, in vehicle scheduling and routing is crucial for safety driving and protecting the interests of drivers. This paper addresses the drop-and-pull container drayage problem with flexible assignment of work break, proposing a mixed-integer programming model and an algorithm for solving realistic-sized instances. Experimental results show the effectiveness of the proposed algorithm in handling vehicle scheduling and routing with work break assignment.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
William N. Caballero, Jose Manuel Camacho, Tahir Ekin, Roi Naveiro
Summary: This research provides a novel probabilistic perspective on the manipulation of hidden Markov model inferences through corrupted data, highlighting the weaknesses of such models under adversarial activity and emphasizing the need for robustification techniques to ensure their security.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Davood Zaman Farsa, Shahryar Rahnamayan, Azam Asilian Bidgoli, H. R. Tizhoosh
Summary: This paper proposes a multi-objective evolutionary framework for compressing feature vectors using deep autoencoders. The framework achieves high classification accuracy and efficient image representation through a bi-level optimization scheme. Experimental results demonstrate the effectiveness and efficiency of the proposed framework in image processing tasks.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Matthew E. Scherer, Raymond R. Hill, Brian J. Lunday, Bruce A. Cox, Edward D. White
Summary: This paper discusses instance generation methods for the multidemand multidimensional knapsack problem and introduces a primal problem instance generator (PPIG) to address feasibility issues in current instance generation methods.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Yin Yuan, Shukai Li, Lixing Yang, Ziyou Gao
Summary: This paper investigates the design of real-time train regulation strategies for urban rail networks to reduce train deviations and passenger waiting times. A mixed-integer nonlinear programming (MINLP) model is used and an efficient iterative optimization (IO) approach is proposed to address the complexity. The generalized Benders decomposition (GBD) technique is also incorporated. Numerical experiments show the effectiveness and computational efficiency of the proposed method.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Xinghai Guo, Netirith Narthsirinth, Weidan Zhang, Yuzhen Hu
Summary: This study proposes a bi-level scheduling method that utilizes unmanned surface vehicles for container transportation. By formulating mission decision and path control models, efficient container transshipment and path planning are achieved. Experimental results demonstrate the effectiveness of the proposed approach in guiding unmanned surface vehicles to complete container transshipment tasks.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Review
Computer Science, Interdisciplinary Applications
Jose-Fernando Camacho-Vallejo, Carlos Corpus, Juan G. Villegas
Summary: This study aims to review the published papers on implementing metaheuristics for solving bilevel problems and performs a bibliometric analysis to track the evolution of this topic. The study provides a detailed description of the components of the proposed metaheuristics and analyzes the common combinations of these components. Additionally, the study provides a detailed classification of how crucial bilevel aspects of the problem are handled in the metaheuristics, along with a discussion of interesting findings.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Xudong Diao, Meng Qiu, Gangyan Xu
Summary: In this study, an optimization model for the design of an electric vehicle-based express service network is proposed, considering limited recharging resources and power management. The proposed method is validated through computational experiments on realistic instances.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Ramon Piedra-de-la-Cuadra, Francisco A. Ortega
Summary: This study proposes a procedure to select candidate sites optimally for ensuring energy autonomy and reinforced service coverage for electric vehicles, while considering demand and budget restrictions.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Danny Blom, Christopher Hojny, Bart Smeulders
Summary: This paper focuses on a robust variant of the kidney exchange program problem with recourse, and proposes a cutting plane method for solving the attacker-defender subproblem. The results show a significant improvement in running time compared to the state-of-the-art, and the method can solve previously unsolved instances. Additionally, a new practical policy for recourse is proposed and its tractability for small to mid-size kidney exchange programs is demonstrated.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Anqi Li, Congying Han, Tiande Guo, Bonan Li
Summary: This study proposes a general framework for designing linear programming instances based on the preset optimal solution, and validates the effectiveness of the framework through experiments.
COMPUTERS & OPERATIONS RESEARCH
(2024)
