Robert S. Sullivan

Minimizing absolute and squared deviations of completion times with different earliness and tardiness penalties and a common due date

We consider a single-machine scheduling problem in which all jobs have the same due date and penalties are assessed for both early and late completion of jobs. However, earliness and tardiness are penalized at different rates. The scheduling objective is to minimize either the weighted sum of absolute deviations (WSAD) or the weighted sum of squared deviations (WSSD). For each objective we consider two versions of the problem. In the unconstrained version an increase in the due date does not yield any further decrease in the objective function. We present a constructive algorithm for the unconstrained WSAD problem and show that this problem is equivalent to the two-parallel, nonidentical machine, mean flow-time problem. For the unconstrained WSSD and the constrained WSAD and WSSD problems we propose implicit enumeration procedures based on several dominance conditions. We also report on our computational experience with the enumeration procedures.

A controlled search simulated annealing method for the single machine weighted tardiness problem

In this paper, a new controlled search simulated annealing method is developed for addressing the single machine weighted tardiness problem. The proposed method is experimentally shown to solve optimally 99% of fifteen job problems with less than 0.2 CPU seconds, and to solve one hundred job problems as accurately as any existing methods, but with far less computational effort. This superior performance is achieved by using controlled search strategies that employ a good initial solution, a small neighborhood for local search, and acceptance probabilities of inferior solutions that are independent of the change in the objective function value.

A bottleneck-based beam search for job scheduling in a flexible manufacturing system

In this paper, we study job-scheduling methods for flexible manufacturing systems (FMSs). Routeing flexibility is a feature that distinguishes FMS scheduling from a classic general jobshop problem....

Ranking Dispatching Rules by Data Envelopment Analysis in a Job Shop Environment

This paper uses Data Envelopment Analysis (DEA) to measure multiple performance criteria for 42 dispatching rules in a job shop environment. We introduce a DEA application in production scheduling. Seven performance measures are considered in the evaluation. Without pre-assigning weights to any performance measure, DEA evaluates the efficiency of each dispatching rule relative to the other rules. After running a large number of experiments, the results show that two extreme subgroups of dispatching rules perform consistently. The shortest processing time related rules form the top group, while the longest processing time related rules form the bottom group. The due date or slack-related rules perform well in tardiness. However, they are ranked low if all seven criteria are considered together. The results provide guidance to scheduling practitioners in choosing priority dispatching rules when there are multiple objectives.

Experimental investigation of real-time scheduling in flexible manufacturing systems

This paper presents a new two-phase (TP) approximate method for real-time scheduling in a flexible manufacturing system (FMS). This method combines a reduced enumeration schedule generation algorithm with a 0–1 optimization algorithm. In order to make the combined algorithm practicable, heuristic rules are introduced for the selection of jobs to be scheduled. The relative performance of the TP method vis-a-vis conventional heuristic dispatching rules such as SPT, LPT, FCFS, MWKR, and LWKR is investigated using combined process-interaction/discrete-event simulation models. An efficient experimental procedure is designed and implemented using these models, and the statistical analysis of the results is presented. For the particular case investigated, the conclusions are very encouraging. In terms of mean flow time, the TP method performs significantly better than any other tested heuristic dispatching rules. Also, the experimental results show that using global information significantly improves the FMS performance.

The service sector: Challenges and imperatives for research in operations management

Abstract The United States has undergone a transformation from an industrial society to the first postindustrial society. Consequently, the service sector has outstripped manufacturing in its contribution to the GNP and in employment. This paper discusses the challenges and imperatives for research in service operations management (SOM). Service operations have unique characteristics that must be considered in developing research strategies. Recent attempts at evolving a general theory of service organizations are reviewed, and it is suggested that these conceptual models provide a unifying framework for the study of SOM. Research in SOM requires a broad perspective that includes the customer and the interactions with other functional areas. It requires an integration of conventional production concepts with behavioral and marketing considerations.

Schedule generation in a dynamic job shop

SUMMARY An extension of Giffler and Thompsons algorithm (1960)is developed to create all active schedules in a dynamic job shop. A partitioning scheme is also developed that works extremely well in reducing the number of active schedules created. This reduced enumeration method is much more efficient than the full generation scheme and, based upon the results of test problems, it appears to be nearly as effective.

Dynamic, Non-Preemptive Priority Queues with General, Linearly Increasing Priority Function

This paper considers a single server queueing system that services customers from P non-preemptive priority classes. We assume independent identically distributed exponential interarrival and general service times for each class of customer. We also assume that a customers priority in the queue is determined not only by its class, but also by the length of time it has spent in the queue; the priority for each class can be a general linearly increasing priority function. Our development gives an expression for the expected waiting time of each customer class, and gives bounds on this expression. We demonstrate the calculation of the bounds by several numerical examples, and discuss the sensitivity of the bounds to priority function parameters and system utilization. We also show that, even under the most conservative assumptions, the bounds are remarkably tight. Furthermore, for the special case of an M/M/1 system with identical service time distributions, these bounds can be substantially improved if the ordinal ranking of expected waiting times is known a priori. The results of this research enable systems designers to anticipate and consequently to control system behavior for systems with general linearly increasing priority disciplines.

A knowledge-based system for stacker crane control in a manufacturing environment

A knowledge-based intelligent crane scheduling (INCS) system is developed for controlling a stacker crane in a CIM environment where PCBs are made. INCS involves two types of rules, one for cyclic scheduling, which is shown to be near optimal if there is no machine breakdown, and another for handling machine breakdowns, which adjusts the cyclic schedule to real-time disturbances. After briefly reviewing the literature on knowledge-based systems for manufacturing, the authors describe the problem environment. A framework is used to develop not only INCS but also several other knowledge-based systems that use dispatching rules in place of cyclic schedule. The knowledge-based systems are tested by using data from an existing CIM environment, the feasibility and superiority of INCS are demonstrated, and its advantages and disadvantages are discussed. >

Evaluating the information content of a measure of plant output: An application to high-technology manufacturing

Commonly used measures of plant output have been criticized for their inability to provide information required to manage the dynamic operations of high-technology manufacturing plants. In this paper, we propose tests to evaluate the information content of a measure of plant output that is specifically directed at these issues. These tests are based on recent developments in DATA Envelopment Analysis (DEA), namely the Cone Ratio Envelopments. In this new application of DEA models, we shift the focus from Decision Making Units (DMUs) being evaluated to the DMUs that are being used to effect evaluations. The proposed tests are applied to evaluate the information contnet of a complexity adjusted measure of plant output, which we refer to as Total Net Die Equivalent (TNDE). Developed recently in the context of a high-technology manufacturing plant—a wafer fabrication plant of a merchant semiconductor manufacturing company-TNDE reflects the ongoing changes in product and process technologies, process flow characteristics, and volume of production. Evaluating the information content on joint criteria of “recency” and “efficiency”, the results of our tests, conducted over a 28-month period in the wafer fabrication plant,show that TNDE as a single aggregate (scalar) measure of plant output outperforms the two outputs from which it is synthesized. Thus, TNDE as a single measure of output can be used to provide an improved basis for planning a plants future operations. En route to the development and application of the proposed tests, we illustrate how DEA concepts and models provide a rigorous and systematic basis for conducting ex post technology evaluation to guide continuous improvements in a plants current operations.