Scheduling on a single machine with a single breakdown to minimize stochastically the number of tardy jobs

Jobs with known processing times and due dates have to be processed on a machine which is subject to a single breakdown. The moment of breakdown and the repair time are independent random variables. Two cases are distinguished with reference to the processing time preempted by the breakdown (no other preemptions are allowed): (i) resumption without time losses and (ii) restart from the beginning. Under certain compatible conditions, we find the policies which minimize stochastically the number of tardy jobs.     

A proof for the longest-job-first policy in one-machine scheduling

We consider a one-machine scheduling problem with earliness and tardiness penalties. All jobs are assigned a common due date and the objective is to minimize the total penalty due to job earliness and tardiness. We are interested in finding the optimal combination of the common due-date value and the job sequence. Despite the fact that this problem in general is very hard to solve, we prove that there exists at least a common property for all optimal solutions: The first job in an optimal sequence is one of the longest jobs. We also prove that this property holds for a general class of unimodal penalty functions.     

An evaluation of scheduling heuristics for dynamic single-processor scheduling with early/tardy costs

In an endeavor to broaden the application of scheduling models to decisions involving the use of a manager's time we use simulation to investigate the performance of a number of simple algorithms (including eight priority rules and a construction heuristic) in a dynamic setting with tasks arriving (randomly) and scheduling decisions being made, over time. We compare these simple methods relative to a bound that uses an adjacent pairwise interchange algorithm. We model uncertainty in task durations, and costs being incurred for early and tardy task completion (representative of JIT settings). In addition to evaluating the efficacy of the scheduling rules and various preemption strategies (using ANOVA), we highlight the managerial implications of the effects of eight environmental parameters. © 1996 John Wiley & Sons, Inc.     

Criteria and approximate methods for path-constrained moving-target search problems

A search is conducted for a target moving in discrete time among a finite number of cells according to a known Markov process. The searcher must choose one cell in which to search in each time period. The set of cells available for search depends upon the cell chosen in the last time period. The problem is to find a search path, i.e., a sequence of search cells, that either maximizes the probability of detection or minimizes the mean number of time periods required for detection. The search problem is modelled as a partially observable Markov decision process and several approximate solutions procedures are proposed. © 1995 John Wiley & Sons, Inc.     

Discount pricing policies for inventories subject to declining demand

Until only recently, the mechanism behind determining item price has been ignored and the discount price taken as a given in quantity-discount inventory decision problems. Inventory subject to declining demand further complicates both pricing and replenishment decisions. This article provides the vendor with the means for optimally determining both the discount price and replenishment order frequency for all buyers in the system in an environment of declining demand. In the multiple-buyer case, we provide an efficient algorithm for classifying buyers into homogeneous subgroups to further enhance joint cost savings among all system participants.     

The inventory packing problem

We study the problem of finding the minimum number of identical storage areas required to hold n items for which demand is known and constant. The replenishments of the items within a single storage area may be time phased so as to minimize the maximum total storage capacity required at any time. This is the inventory-packing problem, which can be considered as a variant of the well-known bin-packing problem, where one constraint is nonlinear. We study the worst-case performance of six heuristics used for that earlier problem since the recognition version of the inventory-packing problem is shown to be NP complete. In addition, we describe several new heuristics developed specifically for the inventory-packing problem, and also study their worst-case performance. Any heuristic which only opens a bin when an item will not fit in any (respectively, the last) open bin needs, asymptotically, no more than 25/12 (resp., 9/4) times the optimal number of bins. Improved performance bounds are obtainable if the range from which item sizes are taken is known to be restricted. Extensive computational testing indicates that the solutions delivered by these heuristics are, for most problems, very close to optimal in value.     

Properties of a three-dimensional estimator

A large-scale simulation was conducted to investigate the statistical properties and the suitability of an estimator that estimates the coordinates of a three-dimensional source, according to the angles at which several observers view the source. The estimator uses a heuristical averaging method of estimates obtained from the solution of six two-dimensional problems that utilize line-to-point transformations. The estimator was found to be approximately unbiased with low standard deviations for normal error distributions. An effective and easy-to-use forecasting formula was developed to forecast the parameters of the distributions of the estimates. © 1994 John Wiley & Sons, Inc.     

Note: Pairwise rearrangements in reliability structures

Boland, Proschan, and Tong [2] used the notion of criticality of nodes in a coherent system to study the optimal component arrangement of reliability structures. They also provided a sufficient minimal cut (path) based criterion for verifying the criticality ordering of two nodes. We develop a necessary and sufficient condition for two nodes to be comparable and provide specific examples illustrating our result's applicability. As a corollary, certain optimal arrangement properties of well-known systems are derived. © 1994 John Wiley & Sons, Inc.     

Employment and utilization of engineers among defense contractors

Defense contractors retain engineers for two reasons. First, engineers work on current-period production contracts. Second, engineers conduct independent research and development (IR&D) and write bids and proposals (B&P) for future contracts. The amount of IR&D/B&P activity, however, understates the amount of effort devoted to learning that reduces the cost of future production. Even some engineers who work on current-period production may engage in learning, as a by-product of their efforts. This article develops and implements a model for estimating the volume of learning activity undertaken by four large manufacturers of military aircraft. © 1994 John Wiley & Sons, Inc.     

Using grasp to solve the component grouping problem

Component grouping problems, a type of set-partitioning problem, arise in a number of different manufacturing and material logistics application areas. For example, in circuit board assembly, robotic work cells can be used to insert components onto a number of different types of circuit boards. Each type of circuit board requires particular components, with some components appearing on more than one type. The problem is to decide which components should be assigned to each work cell in order to minimize the number of visits by circuit boards to work cells. We describe two new heuristics for this problem, based on so-called greedy random adaptive search procedures (GRASP). With GRASP, a local search technique is replicated many times with different starting points. The starting points are determined by a greedy procedure with a probabilistic aspect. The best result is then kept as the solution. Computational experiments on problems based on data from actual manufacturing processes indicate that these GRASP methods outperform, both in speed and in solution quality, an earlier, network-flow-based heuristic. We also describe techniques for generating lower bounds for the component grouping problem, based on the combinatorial structure of a problem instance. The lower bounds for our real-world test problems averaged within 7%-8% of the heuristic solutions. Similar results are obtained for larger, randomly generated problems. © 1994 John Wiley & Sons. Inc.