Article
Computer Science, Information Systems
Fred Glover, Zhipeng Lu
Summary: Focal distance tabu search modifies a standard tabu search algorithm for binary optimization by introducing a periodic diversification step. The algorithm combines threshold and lower bound approaches, incorporating focal distance bounds to guide the search towards improving the objective function. This strategy partitions variables into two sets and utilizes abbreviated tabu search processes to drive the search away from a collection of solutions rather than a single solution, enhancing the search efficiency.
SCIENCE CHINA-INFORMATION SCIENCES
(2021)
Article
Management
J. Sanchez-Oro, A. D. Lopez-Sanchez, A. G. Hernandez-Diaz, A. Duarte
Summary: This paper presents a competitive algorithm that combines the Greedy Randomized Adaptive Search Procedure and Tabu Search, along with Strategic Oscillation post-processing, to provide high-quality solutions for the alpha-neighbor p-center problem. Extensive comparison shows the relevance of the proposed algorithm in achieving competitive results.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Zhi Lu, Anna Martinez-Gavara, Jin-Kao Hao, Xiangjing Lai
Summary: This study addresses the capacitated dispersion problem in a weighted graph and proposes an effective and parameter-free heuristic algorithm based on solution-based tabu search. The algorithm employs a fast greedy construction heuristic and utilizes hash functions to identify eligible candidate solutions.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Information Systems
R. Martin-Santamaria, J. Sanchez-Oro, S. Perez-Pelo, A. Duarte
Summary: In the age of connectivity, the constant production of large amounts of data by every person requires effective analysis and extraction of relevant features. This paper proposes a method to divide a set of elements into equally-sized clusters and demonstrates its superiority through computational experiments.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Interdisciplinary Applications
Lei Cai, Xin Wang, Zhixing Luo, Yijing Liang
Summary: This paper studies the problem of electric vehicle relocation and proposes a hybrid algorithm to solve it. The algorithm considers constraints such as time windows, limited durations, and charging requirements, and demonstrates competitive performance in terms of solution quality and solving time.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Management
Said Hanafi, Yang Wang, Fred Glover, Wei Yang, Rick Hennig
Summary: This paper explores various strategies for overcoming local optimality in metaheuristic search. The characteristics of moves are analyzed to make informed decisions on steps that lead away from a local optimum and towards a new local optimum. The authors propose adaptive memory strategies based on exponential extrapolation to identify and take advantage of useful features of solution history. Experimental results on the Quadratic Unconstrained Binary Optimization (QUBO) problem show that the AA algorithm achieves a high solution quality with significantly shorter computation time compared to other algorithms.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Zequn Wei, Jin-Kao Hao
Summary: A multistart solution-based tabu search algorithm was investigated for the NP-hard Set-Union Knapsack Problem, achieving good computational results and shedding light on the key composing ingredients of the algorithm.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Joaquin A. Pacheco, Silvia Casado
Summary: This article presents a resolution method that combines multistart strategies with tabu search for solving the clique partitioning problem. The method allows exploration of unfeasible solutions, which is a novel characteristic. Computational tests show that our method outperforms previous methods in terms of both solution quality and computation time.
APPLIED INTELLIGENCE
(2023)
Article
Engineering, Industrial
Ilias Vlachos, George Malindretos
Summary: This study examines the process of redesigning the aquaculture supply chain to improve market, operational, and sustainability performance. The findings suggest that supply chain redesign should not only involve restructuring the physical network but also extending the value of facilities and integrating information management. By implementing specific interventions, companies can mitigate various types of risks and achieve goals such as reducing lead time and environmental pollution while responding quickly to market demands.
PRODUCTION PLANNING & CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Alejandra Casado, Sergio Perez-Pelo, Jesus Sanchez-Oro, Abraham Duarte
Summary: This research focuses on the maximum intersection of the k-subsets problem (kMIS) and proposes an improved search algorithm with a novel representation method for solutions. Experimental results confirm the superiority of the proposed method.
JOURNAL OF HEURISTICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Bruno Nogueira, Eduardo Tavares, Paulo Maciel
Summary: This paper presents an iterated local search heuristic for solving the weighted vertex coloring problem. The heuristic outperforms other methods in terms of solution quality and computational time, making it a good alternative for large instances that cannot be solved by exact methods.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Awsan Mohammed, Maged S. Al-shaibani, Salih O. Duffuaa
Summary: This paper proposes a novel metaheuristic approach for designing supply chain network problems in the case of multi-objective supply chains. The algorithm hybridizes three meta-heuristic approaches and is combined with a linear programming approach. The proposed algorithm outperforms other algorithms in terms of computational time and performance metrics.
APPLIED SOFT COMPUTING
(2023)
Article
Management
Xi Li, Yanzhi Li, Ying-Ju Chen
Summary: The study examines the effects of strategic inventory in the context of chain-to-chain competition, finding that the role of strategic inventory may be altered or even reversed under such competition. Retailers may increase inventory levels in fiercer competition, intensifying supply chain competition. A prisoner's dilemma can arise in supply chain competition, where manufacturers cannot avoid strategic inventory despite it being potentially harmful.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2022)
Article
Computer Science, Artificial Intelligence
Awsan Mohammed, Salih O. Duffuaa
Summary: This paper investigates the problem of designing supply chains as an important combinatorial optimization problem, and proposes a new efficient hybrid algorithm, GN-TSA, for designing multi-objective supply chain models based on tabu search and generalized network simplex algorithm. The algorithm achieves solutions very close to an exact algorithm with less computation time, outperforming other algorithms in terms of computation time while maintaining the same solution quality.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Pourya Seydanlou, Mohammad Sheikhalishahi, Reza Tavakkoli-Moghaddam, Amir M. Fathollahi-Fard
Summary: This paper presents a practical optimization model for sustainable closed loop supply chain (SCLSC) management in the agricultural industry of Iran, focusing on the olive crop. A metaheuristic algorithm is proposed to solve the complex network design problem and improve the initial solution. The results demonstrate the applicability of the model and the high performance of the proposed algorithm.
APPLIED SOFT COMPUTING
(2023)
Review
Management
Zehranaz Donmez, Bahar Y. Kara, Ozlem Karsu, Francisco Saldanha-da-Gama
Summary: This paper provides a comprehensive review of research on facility location problems under uncertainty in a humanitarian context, with a focus on different perspectives such as facility types, decision-making, optimization criteria, uncertainty capturing methods, and solution methods. The detailed analysis helps identify distinguishing features of the problems and current research trends, expectations, and gaps in existing knowledge, highlighting relevant research directions.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Management
Antonio Diglio, Juanjo Peiro, Carmela Piccolo, Francisco Saldanha-da-Gama
Summary: This paper investigates a districting problem with stochastic demands, aiming to find a balanced division with given probability. A two-phase heuristic method is developed, along with a simulation procedure to estimate the probability of balanced districting. Different probability distributions for demands are also explored.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Computer Science, Interdisciplinary Applications
Yuchen Li, Zixiang Li, Francisco Saldanha-da-Gama
Summary: In this paper, the assembly line rebalancing problem in a multiperiod context with stochastic processing times is studied. Two policies, periodic rebalancing and data-driven rebalancing, are proposed to minimize total costs. Empirical results show that sometimes rebalancing the assembly line is worse, rebalancing too often may not be beneficial, and the new data-driven policy is better than the plain multiperiod policy.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2022)
Article
Mathematics, Applied
Isabel Correia, Teresa Melo
Summary: The study addresses a multi-period facility location problem for two customer segments with distinct service requirements. Two different frameworks for planning capacity decisions are proposed, each with a two-stage stochastic model. Enhanced formulations and additional inequalities are proposed to improve solution efficiency, with extensive computational study showing significant benefits. Important insights into the impact of the two different planning frameworks on facility network configuration and total cost are also provided.
COMPUTATIONAL & APPLIED MATHEMATICS
(2021)
Article
Management
Yuchen Li, Francisco Saldanha-da-Gama, Ming Liu, Zaoli Yang
Summary: This paper investigates a comprehensive production planning problem under uncertain demand, which involves two NP-hard optimization problems: assembly line balancing and capacitated lot-sizing. It proposes efficient solution procedures for risk-averse decision makers and provides insights from a case study related to mask production as well as the results of computational tests.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Information Systems
Chuan Wang, Hongjie Lan, Francisco Saldanha-da-Gama, Youhua Chen
Summary: This study focuses on optimizing a last-mile delivery system with multiple transportation modes, combining vans, drones, and trucks to deliver parcels. The goal is to reduce the overall delivery cost, and results show that nearly 10% of costs can be saved by combining traditional delivery methods with drones and drone stations through the use of a heuristic algorithm and discrete optimization model.
Article
Engineering, Industrial
Javier Alcaraz, Laura Anton-Sanchez, Francisco Saldanha-da-Gama
Summary: This work provides new insights on bi-criteria resource-constrained project scheduling problems. It presents a realistic problem definition and optimization model, followed by the development of an algorithm and a metaheuristic algorithm to solve the problem.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Computer Science, Information Systems
Bowen Zhang, Xiang Li, Francisco Saldanha-da-Gama
Summary: This paper investigates and compares different repositioning rules in free-floating bike-sharing systems. The authors propose new rules and develop mathematical models. Computational tests show that different rules have different cost-effectiveness in various repositioning scenarios.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Interdisciplinary Applications
Isabel Correia, Teresa Melo
Summary: E-commerce growth is leading retailers to adopt flexible alternatives for storage space that allow them to respond dynamically to variations in demand and improve customer service. This paper addresses the configuration problem of a two-echelon, multi-commodity distribution network operated by a retailer, utilizing mixed-integer linear programming and considering alternative approaches with limited flexibility and scalability.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Management
Victor Blanco, Ricardo Gazquez, Francisco Saldanha-da-Gama
Summary: This paper presents a general modeling framework for solving a multi-type maximal covering location problem. The framework simultaneously decides the positions of facilities in different normed spaces to maximize demand. To address the need for intertwining location decisions in discrete and continuous sets, a hybridized problem is considered with facilities located in finite sets and continuous normed spaces. An integer linear programming reformulation is proposed for a natural non-linear model. A branch-and-cut algorithm is developed for better tackling the problem. The study focuses on locating continuous facilities in the Euclidean plane and proposes an alternative integer linear programming model by leveraging geometrical properties. Extensive computational experiments are conducted to evaluate the methodological contribution, including both synthetic and real geographical and demographic data with up to 920 demand nodes. (c) 2022 Elsevier B.V. All rights reserved.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Management
Antonio Diglio, Juanjo Peiro, Carmela Piccolo, Francisco Saldanha-da-Gama
Summary: This work investigates a districting problem with stochastic demand, using chance-constraints to model balancing requirements. Explicit contiguity constraints are also taken into account. An approximate deterministic counterpart is proposed, which forms the basis for new solution algorithms. These algorithms use a locationallocation scheme and offer two variants of a new heuristic. Extensive computational tests were conducted, and the results are reported. (c) 2022 Elsevier B.V. All rights reserved.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Economics
Francisco Saldanha-da-Gama
Summary: This article aims to contribute to the celebration of the 25th Anniversary of Transportation Research Part E: Logistics and Transportation Review by providing an overview of the role of Facility Location in Logistics and Transportation. It discusses the increasing importance of Facility Location due to technological developments, economy globalization, and environmental concerns. The article also explores current trends and future challenges, including the transition from Industry 4.0 to Industry 5.0 and the impact of data-driven decision making in the era of big data.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Management
Angelo Aliano Filho, Washington A. Oliveira, Teresa Melo
Summary: We propose a mixed-integer non-linear programming model to schedule planting and harvesting operations for different varieties of sugarcane, considering constraints related to cultivation and harvesting cycles, machinery availability, and technical requirements. The model aims to maximize sucrose and fiber production, minimize harvesting time, and reduce transportation costs. We develop a tailored exact method that efficiently obtains Pareto-optimal solutions. The computational study demonstrates the effectiveness of the proposed methodology and provides insights for decision-making.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Management
Afaf Aloullal, Francisco Saldanha-da-Gama, Raca Todosijevi
Summary: This research investigates the use of time-dependent decisions in hub-location routing. The study proposes a mathematical model that can solve the problem optimally for small instances and a matheuristic for larger instances. The results suggest that considering time in the decision-making process can lead to better solutions that can handle parameter changes throughout time. Moreover, the proposed methodology can be easily adapted to other multi-period decision-making problems and different objective functions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Tianqi Liu, Francisco Saldanha-da-Gama, Shuming Wang, Yuchen Mao
Summary: This work focuses on a class of facility location problems with state-dependent demand uncertainty. The authors adopt a state-wise ambiguity set to model distributional uncertainty in different states. They analyze the impact of the change in ambiguity-set parameters on the total cost and location design using robust sensitivity analysis. They propose a nested Benders decomposition algorithm for solving the model exactly. The numerical experiments demonstrate the value and robustness of the model and the performance of the solution approach.
INFORMS JOURNAL ON COMPUTING
(2022)
Article
Engineering, Industrial
Hiroshi Matsuhisa, Nobuo Matsubayashi
Summary: This study investigates the formation of an alliance between competing manufacturers and a monopolistic platform retailer, and analyzes the impact of the degree of differentiation among manufacturers on the formation of the alliance and the profitability of the retailer.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Lingxuan Kong, Ge Zheng, Alexandra Brintrup
Summary: Supply Chain Financing is used to optimize cash flows in supply networks, but recent scandals have shown inefficiencies in risk evaluation. This paper proposes a Federated Learning framework to address order-level risk evaluation.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Jing Gu, Xinyu Shi, Junyao Wang, Xun Xu
Summary: The asymmetric market power between a firm and its partners negatively affects the firm's financial performance. Building relationships with suppliers or customers that have matched market power is the best approach. The strength of the buyer-supplier relationship amplifies the negative impact of asymmetric market power, while the level of relationship embeddedness reduces its negative effect. Moreover, firm-specific institutional, industry, and regional economic heterogeneities also influence the financial impact of asymmetric market power.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Yu Du, Jun-qing Li
Summary: This study investigates the group scheduling of a distributed flexible job shop problem using the concrete precast process. The proposed solution utilizes three coordinated double deep Q-networks (DQN) as a learn-to-improve reinforcement learning approach. The algorithm shows superiority in minimizing costs and energy consumption.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Xiaoyu Yan, Weihua Liu, Ou Tang, Jiahe Hou
Summary: This study analyzes the market amplification effect and the impact of entrant's overconfidence on a two-sided platform. The results show that overconfident entrants can lead to price increases and benefit both the existing firms and themselves to a certain extent.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Illya Kaynov, Marijn van Knippenberg, Vlado Menkovski, Albert van Breemen, Willem van Jaarsveld
Summary: The One-Warehouse Multi-Retailer (OWMR) system is a typical distribution and inventory system. Previous research has focused on heuristic reordering and allocation strategies, which are time-consuming and problem-specific. This paper proposes a Deep Reinforcement Learning (DRL) algorithm for OWMR problems, which infers a multi-discrete action distribution and improves performance with a random rationing policy.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Yimeng Sun, Ruozhen Qiu, Minghe Sun
Summary: This study considers a multi-period inventory management problem for a retailer offering limited-time discounts and having a joint service-level requirement under demand uncertainty. It proposes a double-layer iterative approach to solve the problem and maximize total profit while balancing the service level using a posteriori method and an affinely adjustable robust chance-constrained model.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Anas Neumann, Adnene Hajji, Monia Rekik, Robert Pellerin
Summary: This paper presents a new mathematical formulation for planning and scheduling activities of Engineer-To-Order (ETO) projects, along with a new ETO strategy to reduce the impacts of design uncertainty. The study proposes a hybrid Layered Genetic Algorithm combined with an adaptive Lamarckian learning process (LLGA) and compares it with the branch-and-cut procedure of CPLEX. The results show good performance of the proposed mathematical model for small and medium-sized instances.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Thilini Ranasinghe, Chanaka D. Senanayake, Eric H. Grosse
Summary: Production systems are undergoing transformative changes, necessitating adaptability from human workers. This study developed an analytical model to account for stochastic processing times and learning heterogeneity, revealing insights into system performance.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Sunil Tiwari, Pankaj Sharma, Ashish Kumar Jha
Summary: Black Swan events such as the COVID-19 pandemic and the Suez Canal blockage have a significant impact on firms' technology adoption decisions, especially in terms of disruptions and digitalization in the supply chains. This study investigates the influence of institutional forces and environmental contingencies on supply chain digitalization from an institutional and contingency theory perspective. The findings emphasize the importance of organizational readiness and people readiness, including top management involvement and employee training, in facilitating digitalization.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Fabio Neves-Moreira, Pedro Amorim
Summary: Omnichannel retailers are using stores as distribution centers to provide faster online order fulfillment services. However, in-store picking operations can impact the offline customer experience. To address this, we propose a Dynamic In-store Picker Routing Problem (diPRP) that minimizes customer encounters while fulfilling online orders. Our solution approach combines mathematical programming and reinforcement learning to find efficient picking policies that reduce customer encounters.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Richard Kraude, Ram Narasimhan
Summary: In this study, the relationship between Vertical Integration (VI) and Environmental Performance (EP) is examined, revealing that highly integrated firms produce less waste but engage in fewer environmental initiatives. These findings are crucial for understanding the impact of stakeholder exposure on organizational behavior.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Review
Engineering, Industrial
Korina Katsaliaki, Sameer Kumar, Vasilis Loulos
Summary: This research conducts a systematic literature review (SLR) and content analysis on Supply Chain Coopetition (SCC) through the PRISMA framework. It examines the theory of coopetition and organizational relationships in intra-firm and inter-firm supply chains, focusing on collaboration between rival manufacturers. The study identifies structures and mechanisms of coopetition, such as buyer-supplier coopetition, supply networks coopetition, and production and distribution/logistics coopetition. It provides a holistic approach to SCC management practices and serves as a guide for future research.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)