Maintenance scheduling for modular systems: Modeling and algorithms

We study new models of scheduled maintenance management for modular systems, consisting of multiple components with respective cycle limits. The cycle limit of each component specifies the time interval in which this component must be repaired or replaced. The goal is to compute a feasible maintenance schedule that minimizes the cost associated with component maintenance. Applications of these models arise in Air Force aircraft maintenance as well as in other arenas with required preventive maintenance. The typical cost structures that arise in practical settings are submodular, which make the resulting models computationally challenging. We develop two efficient and operationally tenable approximation algorithms. We prove constant factor worst‐case guarantees for both algorithms, and present computational experiments showing that these algorithms perform within a few percent of optimality on operationally relevant instances. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 472–488, 2014     

Exact algorithms for integrated facility location and production planning problems

We consider a class of facility location problems with a time dimension, which requires assigning every customer to a supply facility in each of a finite number of periods. Each facility must meet all assigned customer demand in every period at a minimum cost via its production and inventory decisions. We provide exact branch‐and‐price algorithms for this class of problems and several important variants. The corresponding pricing problem takes the form of an interesting class of production planning and order selection problems. This problem class requires selecting a set of orders that maximizes profit, defined as the revenue from selected orders minus production‐planning‐related costs incurred in fulfilling the selected orders. We provide polynomial‐time dynamic programming algorithms for this class of pricing problems, as well as for generalizations thereof. Computational testing indicates the advantage of our branch‐and‐price algorithm over various approaches that use commercial software packages. These tests also highlight the significant cost savings possible from integrating location with production and inventory decisions and demonstrate that the problem is rather insensitive to forecast errors associated with the demand streams. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Using real options analysis to value reoptimization options in the shifting bottleneck heuristic

The reoptimization procedure within the shifting bottleneck (SB) involves reevaluation of all previously scheduled toolgroup subproblems at each iteration of the SB heuristic. A real options analysis (ROA) model is developed to value the option to reoptimize in the SB heuristic, such that reoptimization only occurs when it is most likely to lead to a schedule with a lower objective function. To date, all ROA models have sought to value options financially (i.e., in terms of monetary value). The ROA model developed in this paper is completely original in that it has absolutely no monetary basis. The ROA methodologies presented are shown to greatly outperform both full and no reoptimization approaches with respect to both computation time and total weighted tardiness. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Minimal forecast horizon procedures for dynamic lot size models

This article presents new results which should be useful in finding production decisions while solving the dynamic lot sizing problem of Wagner–Whitin on a rolling horizon basis. In a rolling horizon environment, managers obtain decisions for the first period (or the first few periods) by looking at the forecasts for several periods. This article develops procedures to find optimal decisions for any specified number of initial periods (called planning horizon in the article) by using the forecast data for the minimum possible number of future periods. Computational results comparing these procedures with the other procedures reported in the literature are very encouraging.     

Quantifying optimal mesh and ring design costs

During the last decade telecommunication operators have been deploying WDM (Wavelength Division Multiplexing) technology to satisfy the exponential growth in global communication. While facilitating the advanced information society of today, this has also led to a higher dependency on the networks, and furthermore the high capacity utilization of optical fibers means that a single link failure will influence many users and enterprises. For these reasons, protection of network connections has become a major competitive parameter for the operators. Currently, the most popular protection method is ring protection, due to its simplicity, requiring only basic management functionality and operating with local restoration control. While many optical rings have been deployed, little work has been published on exactly what the cost of ring networks are, compared to general mesh networks. In this article we perform a quantitative comparison between ring protection and mesh protection, using real world network data and realistic prices for network components. Extending classic LP flow models to take rings and node costs into account, and using a link‐path based mesh network LP model, we are able to perform a total cost comparison of the two architectures, and of manual ring network design. The results suggest that the price of mesh network components must be reduced significantly to be competitive with ring based networks, and also that manual network design does not necessarily lead to the most cost‐efficient designs. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2005