Article
Engineering, Chemical
Congqin Ge, Lifeng Zhang, Wenhui Yang, Zhihong Yuan
Summary: Traditional supply chains are becoming more volatile, leading to an increasing adoption of mobile modularization. This allows for flexible capacity adjustments and facility relocations to tackle market volatility. A mixed-integer linear programming model is proposed for closed-loop supply chain network planning with modular distribution and collection facilities. The model is further extended to incorporate uncertain customer demands and recovery rates, and is efficiently solved using a tailored stochastic dynamic dual integer programming approach. Computational experiments demonstrate the effectiveness of the proposed algorithm and the benefits of mobile modules in high temporal and spatial variability of customer demand.
Article
Green & Sustainable Science & Technology
Lida Safari, Seyed Jafar Sadjadi, Farzad Movahedi Sobhani
Summary: This paper addresses the issue of resilient sustainable supply chain design and planning under supply disruption risk. A multi-objective robust model is developed to solve the problem, considering various decisions related to supply chain design and planning. The proposed resilience strategies are found to be efficient in mitigating supply disruptions and maintaining supply chain sustainability.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Review
Management
Alexander Shapiro
Summary: This tutorial discusses modeling and solving multistage stochastic programming problems, focusing on distributionally robust and risk averse approaches. It also explores the concept of time consistency, aiming to present a certain viewpoint on multistage stochastic optimization rather than providing a comprehensive survey of the topic.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Samira Mokhtar, Parisa A. Bahri, Mahdi Shahnazari
Summary: This paper presents a multi-period decision-making framework for procurement managers to develop an optimal supply inventory strategy under uncertain supply conditions. By incorporating financial options valuation techniques, American options valuation method, and Monte Carlo simulation technique, the model remains robust to various stochastic variables influencing inventory management decisions. A case study based on dairy supply chain data demonstrates how decision-makers can appropriately incorporate uncertainties into the decision-making framework.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Shujin Hou, Ying Fan, Bo-Wen Yi
Summary: This paper explores the crucial role of renewable energy in mitigating climate change and the challenges faced in electricity transition planning. Through the development of a new multistage stochastic mixed-integer model, the scalability and computational efficiency issues in model application have been effectively addressed.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Economics
A. M. P. Santos, Kjetil Fagerholt, Gilbert Laporte, C. Guedes Soares
Summary: This paper presents a methodology to solve the Supply Vessel Planning Problem with Stochastic Demands (SVPPSD), which uses a two-stage stochastic programming with recourse algorithm. By accounting for the cost of recourse and exploring a wider solution space, robust schedules with a smaller fleet size can be achieved, leading to significant cost savings.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Environmental Sciences
Kazi Safowan Shahed, Abdullahil Azeem, Syed Mithun Ali, Md Abdul Moktadir
Summary: This study develops a mathematical model to mitigate disruptions in a three-stage supply chain network subject to natural disasters like COVID-19 pandemic. By providing appropriate inventory policies, manufacturers can maximize profits while considering potential disruptions.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Management
Yi Li, Rui Zheng, Ju'e Guo
Summary: This paper examines the sourcing problem of two competing manufacturers in two supply chains and investigates the impact of upstream supply chain structures on manufacturers' performance. By comparing two representative configurations, the authors derive the manufacturers' equilibrium sourcing strategies and demonstrate that competition decreases the incentives for dual sourcing.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2022)
Article
Engineering, Biomedical
Doran Wood, Sila Cetinkaya, Harsha Gangammanavar, Weigo Lu, Jing Wang
Summary: This study aims to develop optimization models and methods that adapt treatment decisions across multiple fractions by utilizing predictions of tumor evolution. By introducing a nonuniform allocation scheme, we demonstrate the superiority of this approach across multiple performance metrics.
PHYSICS IN MEDICINE AND BIOLOGY
(2022)
Article
Engineering, Industrial
Shanshan Li, Yong He, Stefan Minner
Summary: This study explores alternative measures for dealing with supply disruptions in a make-to-order supply chain, focusing on optimizing the response strategies. Analytical guidance on dynamically adjusting sourcing quantity, compensation pricing, and inventory consumption speed is provided. The research suggests that pure strategies are effective for short-term shortages, while combined strategies are more suitable for long-term disruptions.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Hongtao Hu, Shuyuan Guo, Yichen Qin, Wenjin Lin
Summary: This paper investigates the supply chain network design problem and risk mitigation strategy in the context of uncertain supply disruption risk in the aircraft manufacturing industry. A two-stage stochastic programming model is formulated to optimize decisions for supplier selection, strategic partnership establishment, and quantities of production and transportation under uncertain supply disruptions. An improved Benders decomposition algorithm incorporating heuristic searching mechanism is designed to enhance computational efficiency. The computational results demonstrate the effectiveness of the proposed algorithm in terms of accuracy and convergence efficiency, providing practical values to the aircraft manufacturing industry in managing supply risk.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Engineering, Industrial
Mohammad Fattahi, Kannan Govindan, Mehdi Farhadkhani
Summary: This paper explores the design and planning of a supply chain system for power generation from biomass. By developing a two-stage stochastic programming model, the study analyzes various factors affecting the system, including social and environmental aspects. Through social life cycle assessment (S-LCA), the social impact is quantified and sustainability is improved by reducing environmental risks. The research findings demonstrate the effectiveness of the stochastic model in assessing economic potential and guiding the planning of the supply chain system.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Computer Science, Software Engineering
O. Dowson, D. P. Morton, A. Downward
Summary: We propose an algorithm for solving a class of bi-objective multistage stochastic linear programs and develop a new variant of the stochastic dual dynamic programming algorithm by exploiting the structure of the cost-to-go functions as saddle functions. We apply our algorithm to a hydro-thermal scheduling problem using data from the Brazilian Interconnected Power System and propose a computationally tractable heuristic for bi-objective stochastic convex programs.
MATHEMATICAL PROGRAMMING
(2022)
Article
Management
Vincent Guigues, Anatoli Juditsky, Arkadi Nemirovski
Summary: This paper introduces a new class of decision rules, Constant Depth Decision Rules (CDDRs), for multistage optimization under linear constraints with uncertainty-affected right-hand sides. It demonstrates through mathematical models and application examples the effectiveness of these decision rules in solving complex problems.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Soumya Ranjan Pathy, Hamed Rahimian
Summary: Motivated by the disruptions in the global supply chain due to COVID-19, this study investigates the optimal procurement and inventory decisions in a pharmaceutical supply chain with uncertain and spatiotemporal demand. A two-stage optimization framework is proposed to address demand uncertainty, where the first stage minimizes the cost and risk associated with pre-positioning drugs, and the second stage minimizes the cost of recourse decisions. The study considers different risk preferences and proposes two models, stochastic programming and robust optimization, to capture the risk of demand uncertainty. Efficient algorithms are also proposed for solving these models.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Education, Scientific Disciplines
Jennifer Chung, Andrea Obi, Ryan Chen, Wandi Lin, Siyuan Sun, Zixiao Chen, Anurag Gulati, Xun Xu, William Pozehl, F. Jacob Seagull, Amy M. Cohn, Mark S. Daskin, Rishindra M. Reddy
JOURNAL OF SURGICAL EDUCATION
(2015)
Article
Computer Science, Information Systems
Kayse Lee Maass, Mark S. Daskin
Article
Engineering, Industrial
Mark S. Daskin, Emily L. Tucker
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2018)
Article
Operations Research & Management Science
Ashley Davis, Sanjay Mehrotra, Jane Holl, Mark S. Daskin
ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH
(2014)
Article
Automation & Control Systems
Saif Benjaafar, Yanzhi Li, Mark Daskin
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2013)
Article
Management
Jonathan P. Turner, Heron E. Rodriguez, Debra A. DaRosa, Mark S. Daskin, Amanda Hayman, Sanjay Mehrotra
Article
Management
Michael K. Lim, Achal Bassamboo, Sunil Chopra, Mark S. Daskin
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2013)
Article
Management
Federico Liberatore, Maria P. Scaparra, Mark S. Daskin
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2012)
Article
Public, Environmental & Occupational Health
Kayse Lee Maass, Abigail R. Smith, Emily L. Tucker, Hannah Schapiro, Sabrina M. Cottrell, Evelyn Gendron, Peg Hill-Callahan, Stephen J. Gill, Mark S. Daskin, Robert M. Merion, Alan B. Leichtman
PATIENT EDUCATION AND COUNSELING
(2019)
Article
Engineering, Industrial
Emily L. Tucker, Mark S. Daskin, Burgunda Sweet, Wallace J. Hopp
Article
Management
Ece Sanci, Mark S. Daskin
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2019)
Article
Health Policy & Services
Jonathan Turner, Kibaek Kim, Sanjay Mehrotra, Debra A. DaRosa, Mark S. Daskin, Heron E. Rodriguez
HEALTH CARE MANAGEMENT SCIENCE
(2013)
Article
Social Sciences, Mathematical Methods
Jonathan P. Turner, Soonhui Lee, Mark S. Daskin, Tito Homem-de-Mello, Karen Smilowitz
COMPUTATIONAL MANAGEMENT SCIENCE
(2012)