Production planning of style goods with high setup costs and forecast revisions
Operations Research
Journal of Optimization Theory and Applications
Optimality of zero-inventory policies for unreliable manufacturing systems
Operations Research
A theory of rolling horizon decision making
Annals of Operations Research
An asymptotic analysis of hierarchical control of manufacturing systems under uncertainty
Mathematics of Operations Research
Numerical methods for stochastic control problems in continuous time
Numerical methods for stochastic control problems in continuous time
Turnpike sets and their analysis in stochastic production planning problems
Mathematics of Operations Research
Inventory control in a fluctuating demand environment
Operations Research
TD-Gammon, a self-teaching backgammon program, achieves master-level play
Neural Computation
Hierarchical decision making in stochastic manufacturing systems
Hierarchical decision making in stochastic manufacturing systems
Optimal feedback production planning in a stochastic N-machine flowshop
Automatica (Journal of IFAC)
Minimax production planning in failure-prone manufacturing systems
Journal of Optimization Theory and Applications
Robust and optimal control
Average cost optimality in inventory models with Markovian demands
Journal of Optimization Theory and Applications
Optimal production planning in a stochastic manufacturing system with long-run average cost
Journal of Optimization Theory and Applications
Information distortion in a supply chain: the bullwhip effect
Management Science - Special issue on frontier research in manufacturing and logistics
Scheduling of an unreliable manufacturing system with nonresumable setups
Computers and Industrial Engineering - Special issue: new advances in analysis of manufacturing systems
Model-based predictive control for generalized production planning problems
Computers in Industry - Special issue: ASI '95
Existence of optimal feedback production plans in stochastic flowshops with limited buffers
Automatica (Journal of IFAC)
Peeling layers of an onion: inventory model with multiple delivery modes and forecast updates
Journal of Optimization Theory and Applications
Dynamic Programming and Optimal Control
Dynamic Programming and Optimal Control
Reinforcement Learning
Business Dynamics
Model Predictive Control in the Process Industry
Model Predictive Control in the Process Industry
Digital Control of Dynamic Systems
Digital Control of Dynamic Systems
Neuro-Dynamic Programming
A Network Design Problem for a Distribution System with Uncertain Demands
SIAM Journal on Optimization
Discrete Event Dynamic Systems
Least Squares Policy Evaluation Algorithms with Linear Function Approximation
Discrete Event Dynamic Systems
Manufacturing & Service Operations Management
Optimal and Hierarchical Controls in Dynamic Stochastic Manufacturing Systems: A Survey
Manufacturing & Service Operations Management
Dynamic Programming
Integrating Replenishment Decisions with Advance Demand Information
Management Science
Inventory Models with Fixed Costs, Forecast Updates, and Two Delivery Modes
Operations Research
Optimal Replenishment Policies for Multiechelon Inventory Problems Under Advance Demand Information
Manufacturing & Service Operations Management
Learning Algorithms for Separable Approximations of Discrete Stochastic Optimization Problems
Mathematics of Operations Research
Inventory Control with Limited Capacity and Advance Demand Information
Operations Research
SIAM Journal on Control and Optimization
Dynamic-Programming Approximations for Stochastic Time-Staged Integer Multicommodity-Flow Problems
INFORMS Journal on Computing
Dynamic Version of the Economic Lot Size Model
Management Science
Optimal Policies for a Multi-Echelon Inventory Problem
Management Science
Optimal Service Control of a Serial Production Line with Unreliable Workstations and Random Demand
Automatica (Journal of IFAC)
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Brief Manufacturing systems with random breakdowns and deteriorating items
Automatica (Journal of IFAC)
Distributed receding horizon control for multi-vehicle formation stabilization
Automatica (Journal of IFAC)
Guaranteed cost control for multi-inventory systems with uncertain demand
Automatica (Journal of IFAC)
On the minimax reachability of target sets and target tubes
Automatica (Journal of IFAC)
Simulation of production and transportation planning with uncertainty and risk
WSEAS Transactions on Computers
Simulation of the production and distribution planning with risk
ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
Linear-quadratic optimal control strategy for periodic-review inventory systems
Automatica (Journal of IFAC)
A multi-agent knowledge model for SMEs mechatronic supply chains
Journal of Intelligent Manufacturing
Automatica (Journal of IFAC)
Hybrid simulation and optimization approach to design and control fresh product networks
Proceedings of the Winter Simulation Conference
SCOlog: A logic-based approach to analysing supply chain operation dynamics
Expert Systems with Applications: An International Journal
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Supply chains are complicated dynamical systems triggered by customer demands. Proper selection of equipment, machinery, buildings and transportation fleets is a key component for the success of such systems. However, efficiency of supply chains mostly depends on management decisions, which are often based on intuition and experience. Due to the increasing complexity of supply chain systems (which is the result of changes in customer preferences, the globalization of the economy and the stringy competition among companies), these decisions are often far from optimum. Another factor that causes difficulties in decision making is that different stages in supply chains are often supervised by different groups of people with different managing philosophies. From the early 1950s it became evident that a rigorous framework for analyzing the dynamics of supply chains and taking proper decisions could improve substantially the performance of the systems. Due to the resemblance of supply chains to engineering dynamical systems, control theory has provided a solid background for building such a framework. During the last half century many mathematical tools emerging from the control literature have been applied to the supply chain management problem. These tools vary from classical transfer function analysis to highly sophisticated control methodologies, such as model predictive control (MPC) and neuro-dynamic programming. The aim of this paper is to provide a review of this effort. The reader will find representative references of many alternative control philosophies and identify the advantages, weaknesses and complexities of each one. The bottom line of this review is that a joint co-operation between control experts and supply chain managers has the potential to introduce more realism to the dynamical models and develop improved supply chain management policies.