Constraint Programming for Scheduling

Our goal is to introduce the constraint programming (CP) approach within the context of scheduling. We start with an introduction to CP and its distinct technical vocabulary. We then present and illustrate a general algorithm for solving a CP problem with a simple scheduling example. Next, we review several published studies where CP has been used in scheduling problems so as to provide a feel for its applicability. We discuss the advantages of CP in modeling and solving certain types of scheduling problems. We then provide an illustration of the use of a commercial CP tool (OPL Studio) in modeling and designing a solution procedure for a classic problem in scheduling. We conclude with our speculations about the future of scheduling research using this approach

A Major Appliance Manufacturer Rethinks its Inventory Policies for Service Vehicles

A major appliance manufacturer needed to effectively manage $7 million in inventories of repair and replacement parts housed in more than 1,300 service vehicles used for warranty repairs. The manufacturer wanted to optimize the inventories while ensuring that its technicians carried the parts they needed to repair customers’ appliances on the first visit. Typically, service vehicles carry only 400 of the 70,000 parts stocked centrally. Thus, the appropriate composition of vehicle stock is essential to attain acceptable levels of service and costs. We developed and applied an intuitive, efficient, effective, and easy-to-implement heuristic solution to this vehicle-stocking problem and found that the firm could trim more than$3 million per year from its warranty repair costs and increase its first-visit repair rate from 86 percent to 90 percent. The results of a pilot study supported these findings, and we estimated a payback of less than two years on full-scale implementation. The manufacturer is implementing these improved vehicle-stocking policies across its national network

The impact of just-in-time implementation and ISO 9000 certification on total quality managment

In this paper, we examine the impact of just-in-time (JIT) implementation and International Standards Organization (ISO) 9000 certification (as specified by the original standards of the early 1990s) on quality management effects of manufacturing firms. Responding firms in the study were grouped into four categories based on their ISO 9000 and JIT orientation: 1) firms that are ISO 9000 certified but have not implemented JIT (ISO firms); 2) firms that are ISO 9000 certified and have implemented JIT (ISO-JIT films); 3) firms that have implemented JIT but are not ISO 9000 certified (JIT firms); and 4) firms that have not implemented JIT and are not ISO 9000 certified (traditional firms). These groups were compared along 13 plant-level total quality management (TQM) implementation elements and five TQM outcome measures using MANCOVA procedure. Analyses resulted in distinct sets of firms reflecting the impact of the ISO-JIT orientation on its TQM implementation and TQM outcomes. Results support the contingency view that a firm\u27s ability to implement effective TQM practices is enhanced: 1) marginally by ISO 9000 efforts; 2) significantly by JIT implementation; and 3) most by conjoint ISO-JIT efforts (though not much more significantly than JIT implementation alone). These insights have significant practical implications for firms investing in JIT implementation, ISO 9000 certification, and TQM implementation. Interestingly, our study conducted in mid-1990s and its empirical findings lend a strong support for the recent transformation of the original ISO 9000 requirements into the current ISO 9001:2000 framework

Maximizing the Effectiveness of a Preventive Maintenance System: An Adaptive Modeling Approach

The dynamic nature of an operating environment, such as machine utilization and breakdown frequency results in changing preventive maintenance (PM) needs for manufacturing equipment. In this paper, we present an approach to generate an adaptive PM schedule which maximizes the net savings from PM subject to workforce constraints. The approach consists of two components: (a) task prioritization based on a multi-logit regression model for each type of PM task, and (b) task rescheduling based on a binary integer programming (BIP) model with constraints on single-skilled and multi-skilled workforce availability. The task prioritization component develops a multi-logit regression for machine failure probability associated with each type of PM task at the beginning of the year, using historical data on machine utilization, PM, and machine breakdowns. At the start of each PM time-bucket (e.g., a month), we use the updated machine failure probability for each candidate PM task to compute its current contribution to net PM savings, which indicates its current priority. The task rescheduling BIP model incorporates the priorities in selecting tasks for the current bucket to maximize PM effectiveness subject to workforce availability, yielding an adaptive and effective PM schedule for each time-bucket of the master PM schedule. We examine the effect of using multi-skilled workforce on the overall PM effectiveness, and also provide an illustration from a newspaper publishing environment to explain the use of the approach. We have developed four heuristic algorithms to yield good solutions to large scale versions of this scheduling problem. The heuristics perform extremely well, and the best heuristic solution is within 1.4% of optimality on an average.preventive maintenance, multi-logit regression, binary integer programming

Operations Research Helps Reshape Operations Strategy at Standard Register Company

Standard Register (SR) Company is a 93-year-old firm leading in high-volume print production of forms and print stationery for major US firms. SR is facing the strategic challenge of minimizing the total landed costs to offer competitive pricing in the highly competitive traditional print market segment. We applied a trio of operations research (OR) techniques to help SR optimally allocate the production orders across its production-distribution network for minimizing the total landed cost: (1) regressions to estimate the cost and time efficiency attributes of various printing presses on print jobs of different types; (2) optimization modeling to determine the optimal order-routing strategy; and (3) simulation modeling of the production-distribution network to assess the effectiveness of optimal and heuristic allocation strategies under uncertainty of customer orders and equipment performance. With an estimated potential annual savings of over $10 million across SR\u27s major product segments in the high-volume rotary production business, the study has resulted in a strategic shift in SR\u27s capacity-allocation policies. SR\u27s executive-leadership team has launched system-wide production-distribution improvement initiatives and expedited efforts to build real-time supply chain decision-support capabilities to support this philosophy