While Stochastic Dominance has been employed in various forms as early as 1932, it has only been since 1969-1970 that the notion has been developed and extensively employed in the area of economics, finance, agriculture, statistics, marketing and operations research.

In this survey, the first-, second-and third-order stochastic dominance rules are discussed with an emphasis on the development in the area since the 1980s.

Stochastic dominance and expected utility: survey and analysis

Survey of scheduling research involving due date determination decisions

Recent research studies of job shop scheduling have begun to examine the interaction between sequencing priorities and the method of assigning due-dates. This paper surveys the tactical aspects of this interaction, focusing primarily on average tardiness as a measure of scheduling effectiveness. The discussion highlights several factors that can affect the performance of dispatching rules, such as the average flow allowance, the due-date assignment method, and the use of progress milestones. A set of simulation experiments illuminates how these factors interact with the dispatching rule, and the experimental results suggest which combinations are most effective in a scheduling system.

Sequencing Rules and Due-Date Assignments in a Job Shop

In this paper, we survey the literature on heuristic priority rule-based job shop scheduling. Priority rules have been intensively investigated over the last 30 years by means of simulation experiments. They are also used in Shop Floor Control software systems. We present a classification, a characterization, and an evaluation of elementary priority rules. Some priority rule-related model extensions are discussed.

A Survey of Priority Rule-Based Scheduling

Scheduling of job shops has been extensively researched over the last three decades and it continues to attract the interests of both academic researchers and practitioners. This paper provides a state-of-the-art survey of the simulation-based research on dynamic job shop scheduling with a distinct emphasis on two important aspects. First, job-shop simulation modeling and experimental considerations are discussed with a review of the different approaches taken in the literature. Second, a review of the different studies is provided with a focus on their findings on the job shop performance criteria of interest. This paper is aimed at both practicing managers and researchers in the area of job shop scheduling because of the following considerations: 1. (i) The number of factors that characterize a job shop is very large and there is considerable variation in modeling and experimentation across the vast number of studies reported. Important research findings relevant to these issues reviewed in this paper would facilitate comparison of the currently available research results and their extension or application to other situations. 2. (ii) A review of the various studies focusing on some of the more important performance criteria should help practitioners in the selection of scheduling rules to match the criterion particularly relevant to their shops. 3. (iii) Recent studies which have modeled job shops as dual-resource constrained systems and assembly shops have been included in this survey for a more comprehensive coverage. A detailed bibliography is included and every effort has been made to make the survey up-to-date.

Dynamic job shop scheduling: A survey of simulation research

This paper describes a simulation study of assigning attainable or predictable due-dates in hypothetical labor and machine constrained job shop settings of varying size and structure. Several predictable due-date assignment rules are developed based on conditional estimates of individual job flow time derived from initial simulation runs. Mean lateness, mean earliness and mean missed due-dates are used as measures of shop performance to compare the various predictable due-date rules under conditions of varying dispatching rules and shop size and structure.

Results indicate that due-dates assigned based on expected job flow time and shop congestion information may provide more attainable due-dates than rules based solely upon job characteristics. In addition, better due-date performance appears to be achieved when due-date oriented dispatching rules are employed and when the shop system is not structurally complex.

A Simulation Study of Predictable Due-Dates

This paper orders in preference various scheduling policies comprised of dispatching and regeneration rules in a multi-level assembly production system. Traditional expected-value statistical and second-degree stochastic dominance preference ordering rules are used to identify the most efficient scheduling policies for risk-averse managers using various measures of performance. The results indicate that selection of an efficient regeneration rule is contingent upon the selection of a dispatching rule and these rules must be selected jointly to develop efficient scheduling policies. For this study, simple intuitively appealing scheduling policies were found to be efficient.

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Evaluating Scheduling Policies in a Multi-Level Assembly System

This paper applies stochastic dominance (SD) preference-ordering criteria to job shop scheduling rules. A simulation model of a hypothetical dual-constrained job shop is used to derive several measures of shop performance for a number of dispatching/due-date scheduling policies. The results presented suggest that previous research conclusions concerning the relative performance of dispatching scheduling rules may need to be reconsidered if production schedulers are risk-averse utility maximizers.

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A stochastic dominance ordering of scheduling rules

Production/operations management (POM) research has traditionally preference ordered alternatives based on the expected values of outcomes for decision making under risk problems. The shortcomings of ignoring the uncertainty or variance of outcomes are discussed. A hypothetical example is provided to illustrate multiple moment and stochastic dominance preference ordering approaches and to demonstrate the theoretical superiority of stochastic dominance. Conclusions concerning the applicability of stochastic dominance approaches for POM research are presented.

Stochastic Dominance: A Methodological Approach to Enhancing the Conceptual Foundations of Operations Management Theory

Most processes consist of several operations Some or all of these operations may have more than one alternative technological method, resulting in an exponential relationship between the number of possible designs and the number of operation alternatives However, some of these designs may not be feasible because of incompatibilities among operation alternatives A feasible process design will include one alternative for each operation in such a way that each operation is compatible with every other operation in the design For identifying these feasible designs, there are two approaches: traditional and morphological The former relies on trial-and-error, expert judgment, and creative thinking and the latter considers, explicitly or implicitly, every possible design This paper presents an efficient algorithm with computational results for identifying all feasible designs based on compatibility considerations The implementation issues, both computational and organizational, are discussed as integral parts of a framework for process design efforts This framework combines the advantages of both the traditional and morphological approaches and mitigates their disadvantages It also facilitates interaction between the expert's judgment and the programmed model

James K. Weeks

Papers

A Simulation Study of Predictable Due-Dates

Evaluating Scheduling Policies in a Multi-Level Assembly System

A stochastic dominance ordering of scheduling rules

Stochastic Dominance: A Methodological Approach to Enhancing the Conceptual Foundations of Operations Management Theory

Long range process design and compatibility among operations