4.6 Article

A tabu search heuristic for redesigning a multi-echelon supply chain network over a planning horizon

期刊

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ijpe.2011.11.022

关键词

Supply chain network redesign; Facility relocation; Metaheuristics; Tabu search; Strategic oscillation

资金

  1. German Academic Exchange Service (DAAD)

向作者/读者索取更多资源

This paper addresses the problem of redesigning a supply chain network with multiple echelons and commodities. The problem belongs to a comprehensive class of network redesign problems previously introduced in the literature. Redesign decisions comprise the relocation of existing facilities to new sites under an available budget over a finite time horizon, the supply of commodities by upstream facilities, the inventory levels at storage facilities, and the flow of commodities through the network. The problem is modeled as a large-scale mixed-integer linear program. Feasible solutions are obtained by using a tabu search procedure that explores the space of the facility location variables. The latter prescribe the time periods in which changes in the network configuration occur. They are triggered by the setup of new facilities, which operate with capacity transferred from the existing facilities, and by closing the latter upon their entire relocation. As the problem is highly constrained, infeasible solutions with excess budget are allowed during the course of the search process. However, such solutions are penalized for their infeasibility. Computational experiments on realistically sized randomly generated instances indicate that this strategic oscillation scheme used in conjunction with tabu search performs very well. (C) 2011 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Review Management

Humanitarian facility location under uncertainty: Critical review and future prospects *

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

Solutions for districting problems with chance-constrained balancing requirements

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

New approaches for rebalancing an assembly line with disruptions

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

Integrated facility location and capacity planning under uncertainty

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

A risk-averse two-stage stochastic programming model for a joint multi-item capacitated line balancing and lot-sizing problem

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

On Optimizing a Multi-Mode Last-Mile Parcel Delivery System with Vans, Truck and Drone

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.

ELECTRONICS (2021)

Article Engineering, Industrial

Bi-objective resource-constrained project scheduling problem with time-dependent resource costs

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

Free-floating bike-sharing systems: New repositioning rules, optimization models and solution algorithms

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

Distribution network redesign under flexible conditions for short-term location planning

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

Multi-type maximal covering location problems: Hybridizing discrete and continuous problems

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

Approximation schemes for districting problems with probabilistic constraints

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

Facility Location in Logistics and Transportation: An enduring relationship

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

Multi-objective optimization for integrated sugarcane cultivation and harvesting planning

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

Multi-period single-allocation hub location-routing: Models and heuristic solutions

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

Robust Stochastic Facility Location: Sensitivity Analysis and Exact Solution

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

Alliance formation between a platform retailer and competing manufacturers in sharing consumer data for product development

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

A federated machine learning approach for order-level risk prediction in Supply Chain Financing

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

Examining the impact of market power discrepancy between supply chain partners on firm financial performance

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

A deep reinforcement learning based algorithm for a distributed precast concrete production scheduling

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

When will an overconfident entrant in the two-sided market do more good than harm?

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

Deep Reinforcement Learning for One-Warehouse Multi-Retailer inventory management

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

A robust optimization approach for inventory management with limited-time discounts and service-level requirement under demand uncertainty

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

Integrated planning and scheduling of engineer-to-order projects using a Lamarckian Layered Genetic Algorithm

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

Effects of stochastic and heterogeneous worker learning on the performance of a two-workstation production system

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

Digitalization & Covid-19: An institutional-contingency theoretic analysis of supply chain digitalization

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

Learning efficient in-store picking strategies to reduce customer encounters in omnichannel retail

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

How does the stakeholder exposure of vertical integration influence environmental performance?

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

Supply chain coopetition: A review of structures, mechanisms and dynamics

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)