Optimal Ordering Policies for Stochastic Inventory Problems with Observed Information Delays

Bensoussan, Alain; Çakanyıldırım, M.; Feng, Qi; Sethi, Suresh P.

doi:10.1111/j.1937-5956.2009.01028.x

Cited by 32 publications

(13 citation statements)

References 17 publications

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“…Recent supply chain models have often focused on contract-theoretic analysis of organizational decisions based on information asymmetry (Bensoussan et al 2009). 6 At the growth stage, OM articles are typically dynamic programming formulations that explore the management of capacity growth under a variety of contexts ranging from loss of aggregate productivity due to hiring (Anderson 2001), technological change (Li et al 2003), and long lead times needed to acquire capacity (Gaimon and Burgess 2003).…”

Section: Operations Management Researchmentioning

confidence: 99%

The Role of Operations Management Across the Entrepreneurial Value Chain

Joglekar

Lévesque

2013

Production and Operations Management

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This special issue contains articles that exemplify the role of operations management across the entrepreneurial value chain. This value chain encompasses all stages of the entrepreneurial phenomenon, including technology commercialization, where discovery, commitment, organization, and growth must take place. We report on a literature search that identifies research questions categorized with respect to topics crucial to operations management scholars and classify these questions under each stage of this value chain. The search guides the development of an evolutionary path for the use of resources, routines, and reputation (3Rs), often lacking in this process, and enables us to propose modeling and topical gaps in the literature. We offer a framework to set up exemplars for operational tradeoffs uniquely associated with the entrepreneurial value chain. We also articulate how five contributed articles in this issue tackle some of these tradeoffs, prior to introducing four perspective pieces. We hope this discussion motivates follow‐on work and triggers a significant increase in the flow of articles that make it to both entrepreneurship and operations management top‐tier academic and practitioner publications.

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Section: Operations Management Researchmentioning

confidence: 99%

The Role of Operations Management Across the Entrepreneurial Value Chain

Joglekar

Lévesque

2013

Production and Operations Management

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“…It takes time to collect, process, validate, and transmit inventory/demand data; therefore, information delays are expected in inventory systems (Bensoussan et al., 2009). Consequently, the most recent inventory information available to the inventory manager is dated when making ordering decisions.…”

Section: Discounted Cost Criterionmentioning

confidence: 99%

A survey of stochastic inventory models with fixed costs: Optimality of (s, S) and (s, S)‐type policies—Discrete‐time case

Perera

Sethi

2023

Production and Operations Management

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Fixed costs of ordering items or setting up a production process arise in many real-life scenarios. In their presence, the most widely used ordering policy in the stochastic inventory literature is the (s, S) policy. Optimality of (s, S) policies and (s, S)-type policies have been examined for various inventory models, including those with the inventory level being reviewed in every period or continuously, finite and infinite horizons, discounted-cost and average-cost criteria, backlogging and lost-sales practices, standard and generalized demands and/or costs, deterministic and stochastic lead times, single-product and multi-product settings, and coordinated pricing-inventory decisions. We comprehensively survey the vast literature accumulated over seven decades in two papers. This paper is devoted to discrete-time models, and the companion paper, also published in this journal issue, reviews continuous-time models. We go over model specifications, proof techniques, specific results, and limitations of the articles published in the literature. We conclude each paper by providing corresponding suggestions for extensions and directions for future research. K E Y W O R D Sdiscounted-and average-cost criteria, discrete-time inventory models, K-convexity, Markovian demand, optimality of (s, S)-type policies CONTENTS

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“…Furthermore, one can write the evolution of the conditional probability in terms of its current value, the current order, and the current observation. However, there are no longer simple optimal policies except in cases of information delay reported in Bensoussan et al (2009) where modified base stock and (s; S) policies are shown to be optimal.…”

Section: Incomplete Inventory Information Models (I3)mentioning

confidence: 99%

Iterative Learning Control

Owens¹

2015

Encyclopedia of Systems and Control

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We explore the problem of identification and control of living cell populations. We describe how de novo control systems can be interfaced with living cells and used to control their behavior. Using computer controlled light pulses in combination with a genetically encoded light-responsive module and a flow cytometer, we demonstrate how in silico feedback control can be configured to achieve precise and robust set point regulation of gene expression. We also outline how external control inputs can be used in experimental design to improve our understanding of the underlying biochemical processes. AbstractModel predictive control (MPC) has become the standard for implementing constrained, multivariable control of industrial continuous processes. These are processes which are designed to operate around nominal steady-state values, which include many of the important processes found in the refining and chemical industries. The following provides an overview of MPC, including its history, major technical developments, and how MPC is applied today in practice. Possible future developments are provided. AbstractInformation and communication complexity of a networked control system identifies the minimum amount of information exchange needed between the decision makers (such as encoders, controllers, and actuators) to achieve a certain objective, which may be in terms of reaching a target state or achieving a given cost threshold. This formulation does not impose any constraints on the computational requirements to perform the communication or control. Both stochastic and deterministic formulations are considered. AbstractThe concept of "information structures" in decentralized control is a formalization of the notion of "who knows what and when do they know it." Even seemingly simple problems with simply stated information structures can be extremely hard to solve. Perhaps the simplest of such unsolved problem is the celebrated Witsenhausen counterexample, formulated by Hans Witsenhausen in 1968. This entry discusses how the information structure of the Witsenhausen counterexample makes it hard and how an information-theoretic approach, which explores the knowledge gradient due to a nonclassical information pattern, has helped obtain insights into the problem. AbstractMulti-agent systems are encountered in nature (animal groups), in various domains of technology (multi-robot networks, mixed robot-human teams) and in various human activities (such as dance and team athletics). Information exchange among agents ranges from being incidentally important to crucial in such systems. Several systems in which information exchange among the agents is either a primary goal or a primary enabler are discussed briefly. Specific topics include power management in wireless communication networks, data-rate constraints, the complexity of distributed control, robotics networks and formation control, action-mediated communication, and multi-objective distributed systems. AbstractThe notion of input to state stability (ISS) qualitatively...

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Optimal Ordering Policies for Stochastic Inventory Problems with Observed Information Delays

Cited by 32 publications

References 17 publications

The Role of Operations Management Across the Entrepreneurial Value Chain

The Role of Operations Management Across the Entrepreneurial Value Chain

A survey of stochastic inventory models with fixed costs: Optimality of (s, S) and (s, S)‐type policies—Discrete‐time case

Iterative Learning Control

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