Strategic Behavior, Workload, and Performance in Task Scheduling

Moray, Neville; Dessouky, Mohamed I.; Kijowski, Brian; Adapathya, Ravi S.

doi:10.1177/001872089103300602

Cited by 97 publications

(49 citation statements)

References 7 publications

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“…Taking into consideration a study by Moray, Dessouky, Kijowski, and Adapathya (1991), algorithm comprehensibility could also imply a very high cognitive workload. Then, as cognitive resources are limited, schedulers could invest fewer cognitive resources in the rescheduling task than when the algorithm is not comprehensible.…”

Section: Algorithm Comprehensibilitymentioning

confidence: 99%

“…To identify complacent behavior it is necessary to compare performances with a standard; in other words, the best performance that operators can achieve. In scheduling, Moray et al (1991) demonstrated that, from a mathematical point of view, humans are not able to attain optimal performance. For this reason, algorithms are compared in pairs, one having a characteristic that could lead to complacent behavior and the other able to determine the maximum human-performance obtainable.…”

Section: Algorithmsmentioning

confidence: 99%

“…In an experimental study, Moray et al (1991) noted that this algorithm is extremely demanding on schedulers in terms of cognitive workload: "This task [scheduling task having time pressure], for which the MH [Moore-Hodgson] gave the correct schedule, was so difficult when the operators knew the rule that their performance collapsed completely, and the task became impossible" (p. 621). For this reason, the MH algorithm is considered not comprehensible, whereas the EDD algorithm is considered comprehensible.…”

Section: Moore-hodgson Algorithm (Mh)mentioning

confidence: 99%

“…Three algorithms have been described. Previous studies allowed us to characterize each algorithm as having result comprehensibility or algorithm comprehensibility (Green & Appel, 1981;Moray et al, 1991;Nakamura & Salvendy, 1988).…”

Section: Earliest Due Date + Shortest Processing Time (Edd+ +Spt)mentioning

confidence: 99%

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The role of algorithm and result comprehensibility of automated scheduling on complacency

Cegarra¹,

Hoc²

2008

Hum Ftrs & Erg Mfg Svc

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Several studies have stressed that even expert operators who are aware of a machine's limits could adopt its proposals without questioning them (i.e., the complacency phenomenon). In production scheduling for manufacturing, this is a significant problem, as it is often suggested that the machine be allowed to build the production schedule, confining the human role to that of rescheduling. This article evaluates the characteristics of scheduling algorithms on human rescheduling performance, the quality of which was related to complacency. It is suggested that scheduling algorithms be characterized as having result comprehensibility (the result respects the scheduler's expectations in terms of the discourse rules of the information display) or algorithm comprehensibility (the complexity of the algorithm hides some important constraints). The findings stress, on the one hand, that result comprehensibility is necessary to achieve good production performance and to limit complacency. On the other hand, algorithm comprehensibility leads to poor performance due to the very high cost of understanding the algorithm. C 2008 Wiley Periodicals, Inc.

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Section: Algorithm Comprehensibilitymentioning

confidence: 99%

Section: Algorithmsmentioning

confidence: 99%

Section: Moore-hodgson Algorithm (Mh)mentioning

confidence: 99%

Section: Earliest Due Date + Shortest Processing Time (Edd+ +Spt)mentioning

confidence: 99%

See 2 more Smart Citations

The role of algorithm and result comprehensibility of automated scheduling on complacency

Cegarra¹,

Hoc²

2008

Hum Ftrs & Erg Mfg Svc

View full text Add to dashboard Cite

show abstract

“…De Keyser, 1995). For instance, Moray et al (1991), using Tulga and Sheridan's (1980) experimental paradigm, found evidence that operators faced with various tasks of different duration prefer to start the longest task first, even though the normative model would require the shortest task to be started first. In a multi-task micro world experiment (combined manual and supervisory control), Kirlik (1993) found evidence that operators are sensitive to the temporal costs of automation and refuse to use an automatic aid if its engagement is associated with a considerable delay.…”

Section: Representation Analyis and Design Of Dynamic Function Schedmentioning

confidence: 99%

Putting time (back) into dynamic function allocation

Hildebrandt¹,

Harrison²

2003

PsycEXTRA Dataset

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This position paper discusses extensions to concepts of Dynamic Function Allocation (DFA) that could improve our understanding of the trade-offs involved in designing and operating humanautomation systems. We suggest that current DFA paradigms, focusing predominantly on allocation along the human-automation resource d imension, may provide an insufficient basis for design decisions as they fail to take account of alternative function management strategies. Of these strategies, Dynamic Function Scheduling (DFS), the allocation of functions along the temporal dimension, i s of particular interest, not least because scheduling is both a mature engineering discipline and a ubiquitous aspect of human behavior. Understanding these scheduling decisions requires consideration of the temporal properties of functions (e.g. continuous, periodic, sporadic, pre-emptable, interleavable), temporal requirements (e.g. deadlines), and the temporal properties of the agents, human or automatic (e.g. service rates, interruption handling, task switch costs, temporal reasoning abilities, control modes). The paper reviews engineering and human factors approaches that could support the representation, analysis and design of DFS.

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Human performance in industrial scheduling: A framework for understanding

MacCarthy

Wilson

Crawford

2001

Hum Ftrs & Erg Mfg Svc

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Planning and scheduling activities have a significant impact on the performance of manufacturing enterprises. Throughout the 1980s there was a belief that computer-led solutions would "solve" complex industrial planning and scheduling problems. However, in most manufacturing organizations, planning and scheduling still require significant human support to ensure effective performance. Although the contribution of these human resources is often highly valued, we are only beginning to develop a coherent body of knowledge that can contribute toward the successful integration of human and computer-based planning and scheduling systems. Here we examine the state of knowledge in this domain and identify the need for field investigations. We present a framework to facilitate research in human and organizational issues in planning and scheduling in manufacturing. A structured and detailed set of research questions is developed to underpin field studies. The framework focuses on understanding the scheduling environment, the process of scheduling, and related performance issues. The application of the framework is illustrated using our own field studies, where a number of specific research questions of practical importance have been identified: what scheduling is, who carries it out, what influences scheduling practice and performance, how schedulers actually schedule, what makes a good scheduler and schedule, and what support is needed. The framework makes a valuable contribution to advancing knowledge in an area of real practical benefit to contemporary manufacturing industry.

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Strategic Behavior, Workload, and Performance in Task Scheduling

Cited by 97 publications

References 7 publications

The role of algorithm and result comprehensibility of automated scheduling on complacency

The role of algorithm and result comprehensibility of automated scheduling on complacency

Putting time (back) into dynamic function allocation

Human performance in industrial scheduling: A framework for understanding

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