Article
Management
Bo Jin, Shunji Tanaka
Summary: This study develops an efficient algorithm for solving a practical variant of the container relocation problem, and demonstrates its superior performance through computational experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Zixiang Li, Ibrahim Kucukkoc, Qiuhua Tang
Summary: This study introduces two methods to address the type II assembly line balancing problem: the exact method IBBRe and the heuristic method IBSe. The results show that both methods outperform the current state-of-the-art iterative beam search and update the upper bounds for long-standing unresolved cases.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Chemistry, Multidisciplinary
Marko Gulic, Livia Maglic, Tomislav Krljan, Lovro Maglic
Summary: Maritime transport is vital for international trade, with seaports playing a crucial role. The increasing importance of container transport in maritime trade has led to the need for efficient container retrieval. This paper focuses on the optimization problem of container relocation in container yards, proposing a new method that utilizes a genetic algorithm to minimize the number of relocations. The method proves to outperform various existing models in resolving the container relocation problem.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Interdisciplinary Applications
Zehao Wang, Qingcheng Zeng
Summary: This paper investigates the AGV dispatching and routing problem in automated container terminals. Through the use of a mixed-integer programming model and a branch-and-bound algorithm, conflict-free routes are generated, enhancing the efficiency of terminal operations. The proposed algorithm performs well in both small and large-scale instances, and is applicable to real-world and dynamic cases.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Green & Sustainable Science & Technology
Yujian Song, Yuting Zhang, Wanli Wang, Ming Xue
Summary: This paper addresses the drop-and-pickup container drayage problem with empty container constraints. A branch and price algorithm is proposed to solve the formulated mixed-integer linear program effectively, achieving significant efficiency and cost savings compared to CPLEX. The experimental results also demonstrate the increasing benefit of the drop-and-pickup mode with higher customer density and fixed cost.
Article
Computer Science, Artificial Intelligence
Akihisa Watanabe, Ryuta Tamura, Yuichi Takano, Ryuhei Miyashiro
Summary: Canonical correlation analysis (CCA) is a multivariate statistical method for extracting mutual information from multiple datasets. We propose a mixed-integer optimization (MIO) approach to improve the interpretability and efficiency of CCA estimation. Our branch-and-bound algorithm based on the generalized eigenvalue problem can find an optimal solution in terms of canonical correlation, outperforming direct application of optimization software. Moreover, our method provides better-quality solutions than forward stepwise selection and L1-regularized estimation in terms of generalization performance.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Environmental Sciences
Kaiqi Liu, Jiangbin Yuan, Wenhe Yan, Chaozhong Yang, Wei Guo, Shifeng Li, Yu Hua
Summary: eLoran is an important backup and supplement for global navigation satellite systems, and pseudorange positioning is a key issue. A new shrink-branch-bound algorithm is proposed to solve the initialization problem of eLoran pseudorange positioning without any initial value information.
Article
Computer Science, Information Systems
Majid Alotaibi
Summary: This study improves the allocation of cloud container resources by using Combined Spider and Honey Bee Optimization (CS-HBO) method. The comparison of various metrics demonstrates the significant advantage of this method in terms of cost.
COMPUTER COMMUNICATIONS
(2022)
Article
Computer Science, Hardware & Architecture
Harvinder Singh, Sanjay Tyagi, Pardeep Kumar
Summary: The study proposed a crow search based load balancing algorithm to address the issue of resource utilization efficiency in cloud environments, and validated it against a standard algorithm. The results showed that the new algorithm excelled in load balancing and emerged as the most optimal load balancing algorithm.
COMPUTERS & ELECTRICAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Dangdang Niu, Bin Liu, Hongming Zhang, Minghao Yin
Summary: This paper presents a branch-and-bound algorithm BABWSCP for solving the weighted sum coloring problem (WSCP), as well as a method BABLS for improving local search. Experimental results demonstrate the effectiveness of these methods in benchmark tests.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Pharmacology & Pharmacy
Wisnu Ananta Kusuma, Zulfahmi Ibnu Habibi, Muhammad Fahmi Amir, Aulia Fadli, Husnul Khotimah, Vektor Dewanto, Rudi Heryanto
Summary: Jamu is a traditional herbal medicine in Indonesia made from various medicinal plants. This study proposes a method using the branch and bound algorithm to optimize a bipartite graph search for discovering the combination or composition of Jamu formulas. The results show that this method is faster and more accurate than a complete search algorithm in finding the composition of plants for Jamu formulas.
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Najme Mansouri, Gholam Reza Khayati, Behnam Mohammad Hasani Zade, Seyed Mohammad Javad Khorasani, Roya Kafi Hernashki
Summary: This study discusses the importance of feature extraction, feature clustering, and feature selection, and proposes two improved versions of the owl search algorithm. The study also presents a new feature extraction technique based on the improved algorithm. The experimental results demonstrate that the improved algorithm has better convergence rate in solving complex problems, and FOCDR shows good performance in feature selection problems.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Management
Johannes Diefenbach, Raik Stolletz
Summary: This study analyzes the assembly line balancing problem with stochastic task times. A sampling approach is developed to ensure line reliability. The research proves that lower bounds for the related deterministic problem can be transformed into lower bounds for the sampling formulation. The study exemplifies the use of these bounds in a reliability-based branch-and-bound algorithm and proposes effective fathoming strategies based on the transformed lower bounds or direct consideration of line reliability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Yifu Li, Xiangtong Qi
Summary: In the service industry, the perception of a service bundle by customers depends not only on the utility of each activity but also on the sequence of activities. This presents an opportunity for service providers to optimize service bundles by manipulating activities and their sequence.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Mathematical & Computational Biology
Lu-Wen Liao
Summary: In the current era of multimedia, television plays a crucial role in transmitting advertising messages, making it the primary source of revenue for the TV industry. The scheduling of commercials on different TV channels to maximize revenue and minimize penalties is a critical issue for TV stations. This study proposes an exact branch and bound algorithm based on the LFJ/EDD rules and network flow methods to schedule commercials with specific service-level requirements while minimizing the maximum lateness. The computational analysis demonstrates the effectiveness of the proposed bounding scheme and the algorithm's ability to obtain optimal solutions.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2022)
Article
Engineering, Industrial
Zhe Liang, Yan He, Tao Wu, Canrong Zhang
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2015)
Article
Green & Sustainable Science & Technology
Yan He, Yufeng Li, Tao Wu, John W. Sutherland
JOURNAL OF CLEANER PRODUCTION
(2015)
Article
Management
Yan He, Tao Wu, Canrong Zhang, Zhe Liang
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2015)
Article
Economics
Zhe Liang, Yuan Feng, Xiaoning Zhang, Tao Wu, Wanpracha Art Chaovalitwongse
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2015)
Article
Economics
Canrong Zhang, Fanrui Xie, Kun Huang, Tao Wu, Zhe Liang
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2017)
Article
Computer Science, Interdisciplinary Applications
Tao Wu, Fan Xiao, Canrong Zhang, Yan He, Zhe Liang
COMPUTERS & OPERATIONS RESEARCH
(2018)
Article
Operations Research & Management Science
Fanrui Xie, Tao Wu, Canrong Zhang
TRANSPORTATION SCIENCE
(2019)
Article
Computer Science, Interdisciplinary Applications
Tao Wu, Zhongshun Shi, Zhe Liang, Xiaoning Zhang, Canrong Zhang
COMPUTERS & OPERATIONS RESEARCH
(2020)
Article
Computer Science, Interdisciplinary Applications
Tao Wu, Zhongshun Shi, Canrong Zhang
Summary: This study proposes a hub location problem with market selection and introduces a mixed integer programming model along with a subgradient-based Lagrangian relaxation method to solve the problem. The proposed method achieves optimal solutions for small-sized test instances and better solution qualities than the commercial software package for large-sized test instances.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Management
Tao Wu, Le Huang, Zhe Liang, Xiaoning Zhang, Canrong Zhang
Summary: In this study, a supervised learning-driven heuristic is proposed to solve the capacitated facility location and production planning problem. The heuristic uses solution values from linear programming relaxation, Dantzig-Wolfe decomposition, and column generation as features and applies a naive Bayes approach to derive an offline-learned oracle. Computational results show that the proposed heuristic outperforms the commercial CPLEX solver and several state-of-the-art methods in terms of solution quality.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Operations Research & Management Science
Tao Wu, Canrong Zhang, Weiwei Chen, Zhe Liang, Xiaoning Zhang
Summary: In this paper, the authors studied a complicated production-distribution problem and proposed an unsupervised learning-driven matheuristic to improve feasible solutions. The computational results showed that the proposed method outperformed the commercial MILP solver and obtained numerous best-known solutions for a related problem.
TRANSPORTATION SCIENCE
(2022)
Article
Computer Science, Interdisciplinary Applications
Tao Wu
Summary: The study proposed a predictive search method that integrates machine learning/advanced analytics, mathematical programming, and heuristic search for capacitated multi-item lot sizing problems. The advanced analytics models are used to divide the solution space into incumbent, superincumbent, and nonincumbent regions, where an analytics-driven heuristic search procedure is applied to build restricted subproblems and solved by a combined mathematical programming technique. The method is proven to converge to the global optimal solution and outperforms other state-of-the-art methods in computational tests based on benchmark problems.
INFORMS JOURNAL ON COMPUTING
(2022)
Article
Computer Science, Interdisciplinary Applications
Tao Wu, Zhe Liang, Canrong Zhang
INFORMS JOURNAL ON COMPUTING
(2018)
Article
Computer Science, Interdisciplinary Applications
Kerem Akartunali, Ioannis Fragkos, Andrew J. Miller, Tao Wu
INFORMS JOURNAL ON COMPUTING
(2016)
Article
Economics
Songyot Kitthamkesorn, Anthony Chen, Seungkyu Ryu, Sathaporn Opasanon
Summary: The study introduces a new mathematical model to determine the optimal location of park-and-ride facilities, addressing the limitations of traditional models and considering factors such as route similarity and user heterogeneity.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2024)