E. Powell Robinson

Flow Coordination and Information Sharing in Supply Chains: Review, Implications, and Directions for Future Research

Advances in information technology, particularly in the e-business arena, are enabling firms to rethink their supply chain strategies and explore new avenues for inter-organizational cooperation. However, an incomplete understanding of the value of information sharing and physical flow coordination hinder these efforts. This research attempts to help fill these gaps by surveying prior research in the area, categorized in terms of information sharing and flow coordination. We conclude by highlighting gaps in the current body of knowledge and identifying promising areas for future research.

The Impact of E-Replenishment Strategy on Make-to-Order Supply Chain Performance

This research investigates the impact of electronic replenishment strategy on the operational activities and performance of a two-stage make-to-order supply chain. We develop simulation-based rolling schedule procedures that link the replenishment processes of the channel members and apply them in an experimental analysis to study manual, semi-automated, and fully automated e-replenishment strategies in decentralized and coordinated decision-making supply chain structures. The average operational cost reductions for moving from a manual-based system to a fully automated system are 19.6, 29.5, and 12.5%, respectively, for traditional decentralized, decentralized with information sharing, and coordinated supply chain structures. The savings are neither equally distributed among participants, nor consistent across supply chain structures. As expected, for the fully coordinated system, total costs monotonically decrease with higher levels of automation. However, for the two decentralized structures, under which most firms operate today, counter-intuitive findings reveal that the unilateral application of e-procurement technology by the buyer may lower his purchasing costs, but increase the sellers and systems costs. The exact nature of the relationship is determined by the channels operational flexibility. Broader results indicate that while the potential economic benefit of e-replenishment in a decentralized system is substantial, greater operational improvements maybe possible through supply chain coordination.

Uncapacitated facility location: General solution procedure and computational experience

Abstract This paper presents a general model and dual-based branch-and-bound solution procedure for finding optimal solutions to the single-echelon, two-echelon, and multi-activity uncapacitated facility location problems. The problem is formulated as an arborescent-fixed-charge network (ARBNET) programming model which visually displays the problems physical and mathematical structure and generalized modeling capabilities. Alternative strategies for implementing the dual-based solution procedure are discussed and the results of computational experiments are given to document their relative efficiency. The computational results indicate that the proposed dual-based solution procedure effectively solves realistic sized single-echelon, two-echelon, and multi-activity location problems. This research takes another step toward the development of an efficient, general purpose decision support system for distribution system planning.

Coordinated Capacitated Lot-Sizing Problem with Dynamic Demand: A Lagrangian Heuristic

Coordinated replenishment problems are common in manufacturing and distribution when a family of items shares a common production line, supplier, or a mode of transportation. In these situations the coordination of shared, and often limited, resources across items is economically attractive. This paper describes a mixed-integer programming formulation and Lagrangian relaxation solution procedure for the single-family coordinated capacitated lot-sizing problem with dynamic demand. The problem extends both the multi-item capacitated dynamic demand lot-sizing problem and the uncapacitated coordinated dynamic demand lot-sizing problem. We provide the results of computational experiments investigating the mathematical properties of the formulation and the performance of the Lagrangian procedures. The results indicate the superiority of the dual-based heuristic over linear programming-based approaches to the problem. The quality of the Lagrangian heuristic solution improved in most instances with increases in problem size. Heuristic solutions averaged 2.52% above optimal. The procedures were applied to an industry test problem yielding a 22.5% reduction in total costs.

Master production schedule time interval strategies in make-to-order supply chains¶

While the literature primarily addresses MPS design from the manufacturers perspective, this research considers MPS policy design in a two-stage rolling schedule environment with a particular focus on the policy governing schedule flexibility in the non-frozen time interval (i.e. liquid versus slushy orders). Using computer simulation, we experimentally evaluate the impact of four MPS design factors (non-frozen interval policy, planning horizon length, frozen interval length and re-planning frequency) and four environmental factors (natural order cycle length, vendor flexibility, demand range and demand lumpiness) on MPS schedule cost and instability. The experimental design considers the often-conflicting impact of MPS policy on the channel members by capturing performance metrics at the manufacturer, vendor and system level. The research findings indicate that moving from a liquid to a slushy non-interval strategy increases the manufacturers costs, but may result in an even greater cost reduction for the vendor resulting in lower system costs. The economic benefit of the slushy strategy is directly tied to the vendors relative flexibility in responding to the manufacturers orders on a lot-for-lot basis. High vendor flexibility favours the liquid strategy, while low vendor flexibility favours the slushy strategy. ¶ This research was partially funded by a grant from the Scholarly Research Grant Program of the College of Business Administration at the University of Tennessee.

A comparative study of modeling and solution approaches for the coordinated lot-size problem with dynamic demand

In the coordinated lot-size problem, a major setup cost is incurred when at least one member of a product family is produced and a minor setup cost for each different item produced. This research consolidates the various modeling and algorithmic approaches reported in the literature for the coordinated replenishment problem with deterministic dynamic demand. For the two most effective approaches, we conducted extensive computational experiments investigating the quality of the lower bound associated with the models linear programming relaxation and the computational efficiency of the algorithmic approaches when used to find heuristic and optimal solutions. Our findings indicate the superiority of the plant location type problem formulation over the traditional approach that views the problem as multiple single-item Wagner and Whitin problems that are coupled by major setup costs. Broader implications of the research suggest that other classes of deterministic dynamic demand lot-size problems may also be more effectively modeled and solved by adapting plant location type models and algorithms.

A comparative model of facility network design methodologies

Abstract Operations managers use a variety of decision making tools when designing facility networks. Intuition, scenario evaluation, heuristic and optimization procedures are commonly applied. This paper discusses the relative advantages and disadvantages of the alternative methodologies for network design and proposes a cost trade-off model for choosing the best approach. Accessibility, precision and supplemental analysis are key factors to consider during the selection process. We also present the results of a laboratory experiment which measured the performance of analysts using intuition, scenario evaluation and enhanced scenario evaluation procedures to solve realistically-sized network design problems. The test problems included several sizes of single-echelon, multi-activity and two-echelon facility network design problems. The experimental results, when embedded into the cost trade-off model, provide quantitative guidelines for selecting the appropriate decision support procedures. Implications for practitioners, researchers and decision support system developers are provided.

Customer Service: Implications for Distribution System Design

The interaction between customer service policy, as defined by the in‐transit delivery lead time component of the order cycle and the design of least cost distribution systems is examined. A broader view of the distribution system design problem than previously taken in the literature is given and both the firm′s network strategy (number and location of facilities) and transportation strategy (mode/method of shipment) into the planning process are incorporated. Procedures for incorporating customer service policy into the distribution system design process are discussed; the effect of alternate customer service definitions on the least cost distribution system design are evaluated; and new mathematical procedures that integrate customer service policy, network strategy and transportation strategy into a comprehensive planning model are provided. Example problems in the text illustrate the potential benefit of accepting premium transportation costs in return for reduced facility proximity to customers.