Abstract:This study considers a typical scheduling environment that is influenced by the behavioral phenomenon of multitasking. Under multitasking, the processing of a selected job suffers from interruption by other jobs that are available but unfinished. This situation arises in a wide variety of applications; for example, administration, manufacturing, and process and project management. Several classical solution methods for scheduling problems no longer apply in the presence of multitasking. The solvability of any … Show more
“…In this section, we formulate multitasking scheduling problems with DRMA and a deterioration effect based on the multitasking setting in Hall et al [14] and the RMA and fatigue effect in Lodree Jr. and Geiger [37] and S.-J. Yang and D.-L. Yang [22].…”
Section: Problem Formulation and Notationmentioning
confidence: 99%
“…Thus, in recent multitasking-related literature, investigation has been made about the effects of multitasking on the productivity from different perspectives [2,[11][12][13]. Yet, considering multitasking in scheduling systems remains relatively unexplored except for the works of Hall et al [14], Sum et al [15], Sum et al [16], and Zhu et al [17]. Hall et al [14] initiated scheduling problems with multitasking by proposing scheduling models in an administration scheduling system.…”
Section: Introductionmentioning
confidence: 99%
“…Yet, considering multitasking in scheduling systems remains relatively unexplored except for the works of Hall et al [14], Sum et al [15], Sum et al [16], and Zhu et al [17]. Hall et al [14] initiated scheduling problems with multitasking by proposing scheduling models in an administration scheduling system. Then, Sum et al [15], Sum et al [16], and Zhu et al [17] extended their work based on the basic setting of a multitasking scheduling model, where the processing of a selected task suffers from interruption by other tasks that are available but unfinished.…”
Section: Introductionmentioning
confidence: 99%
“…Although Hall et al [14] provided a practical administrative planning scenario illustrating scheduling with multitasking, the deterioration effect and DRMA of human operators were not considered. When human operators are multitasking, the deterioration effect and DRMA change the processing times remarkably, which may incur different scheduling results.…”
Section: Introductionmentioning
confidence: 99%
“…Zhu et al [17] investigated the multitasking scheduling problem with RMA, yet they ignored the job deterioration effect and the variability (deterioration) of RMA from human fatigue. Extending the work of Hall et al [14], Lodree Jr. and Geiger [37], and Zhu et al [17], we jointly consider the above issues in human-based scheduling systems to pursue more practical results. We refer to the proposed problem as multitasking scheduling problems with deterioration effect.…”
Multitasking scheduling problems with a deterioration effect incurred by coexisting behavioral phenomena in human-related scheduling systems including deteriorating task processing times and deteriorating rate-modifying activity (DRMA) of human operators are addressed. Under the assumption of this problem, the processing of a selected task suffers from the joint effect of available but unfinished waiting tasks, the position-dependent deterioration of task processing time, and the DRMA of human operators. Traditionally, these issues have been considered separately; herein, we address their integration. We propose optimal algorithms to solve the problems to minimize makespan and the total absolute differences in completion time, respectively. Based on the analysis, some special cases and extensions are also discussed.
“…In this section, we formulate multitasking scheduling problems with DRMA and a deterioration effect based on the multitasking setting in Hall et al [14] and the RMA and fatigue effect in Lodree Jr. and Geiger [37] and S.-J. Yang and D.-L. Yang [22].…”
Section: Problem Formulation and Notationmentioning
confidence: 99%
“…Thus, in recent multitasking-related literature, investigation has been made about the effects of multitasking on the productivity from different perspectives [2,[11][12][13]. Yet, considering multitasking in scheduling systems remains relatively unexplored except for the works of Hall et al [14], Sum et al [15], Sum et al [16], and Zhu et al [17]. Hall et al [14] initiated scheduling problems with multitasking by proposing scheduling models in an administration scheduling system.…”
Section: Introductionmentioning
confidence: 99%
“…Yet, considering multitasking in scheduling systems remains relatively unexplored except for the works of Hall et al [14], Sum et al [15], Sum et al [16], and Zhu et al [17]. Hall et al [14] initiated scheduling problems with multitasking by proposing scheduling models in an administration scheduling system. Then, Sum et al [15], Sum et al [16], and Zhu et al [17] extended their work based on the basic setting of a multitasking scheduling model, where the processing of a selected task suffers from interruption by other tasks that are available but unfinished.…”
Section: Introductionmentioning
confidence: 99%
“…Although Hall et al [14] provided a practical administrative planning scenario illustrating scheduling with multitasking, the deterioration effect and DRMA of human operators were not considered. When human operators are multitasking, the deterioration effect and DRMA change the processing times remarkably, which may incur different scheduling results.…”
Section: Introductionmentioning
confidence: 99%
“…Zhu et al [17] investigated the multitasking scheduling problem with RMA, yet they ignored the job deterioration effect and the variability (deterioration) of RMA from human fatigue. Extending the work of Hall et al [14], Lodree Jr. and Geiger [37], and Zhu et al [17], we jointly consider the above issues in human-based scheduling systems to pursue more practical results. We refer to the proposed problem as multitasking scheduling problems with deterioration effect.…”
Multitasking scheduling problems with a deterioration effect incurred by coexisting behavioral phenomena in human-related scheduling systems including deteriorating task processing times and deteriorating rate-modifying activity (DRMA) of human operators are addressed. Under the assumption of this problem, the processing of a selected task suffers from the joint effect of available but unfinished waiting tasks, the position-dependent deterioration of task processing time, and the DRMA of human operators. Traditionally, these issues have been considered separately; herein, we address their integration. We propose optimal algorithms to solve the problems to minimize makespan and the total absolute differences in completion time, respectively. Based on the analysis, some special cases and extensions are also discussed.
It is well known that the waiting time a customer experiences in a service system is determined by the service processing time of preceding customers, among other factors. We argue that a directionally opposite effect, which diffuses from waiting time to her own service time, also exists in co-productive service contexts where a significant fraction of the service time is contributed by the customer.Multiple underlying customer behavioral mechanisms lead us to hypothesize that waiting's impact is dependent on the service stage and magnifies as the service process approaches completion. Our empirical analysis uses a unique operational data set that combines server log information with instant-messaging transcripts collected from a live-chat contact center. We show that pre-service waiting accelerates customer engagement-one dimension of customer instigated service time-only at the beginning of the conversation and then exhibits a slowdown effect as the conversation proceeds. In contrast, in-service waiting consistently slows down customer responses-another dimension of customer instigated service time, the magnitude of which is higher in later episodes of the agentcustomer message exchanges. We discuss the practical implications of our findings on operational policies employed in contact centers.
We consider the multitasking scheduling problem on unrelated parallel machines to minimize the total weighted completion time. In this problem, each machine processes a set of jobs, while the processing of a selected job on a machine may be interrupted by other available jobs scheduled on the same machine but unfinished. To solve this problem, we propose an exact branch‐and‐price algorithm, where the master problem at each search node is solved by a novel column generation scheme, called in‐out column generation, to maintain the stability of the dual variables. We use a greedy heuristic to obtain a set of initial columns to start the in‐out column generation, and a hybrid strategy combining a genetic algorithm and an exact dynamic programming algorithm to solve the pricing subproblems approximately and exactly, respectively. Using randomly generated data, we conduct numerical studies to evaluate the performance of the proposed solution approach. We also examine the effects of multitasking on the scheduling outcomes, with which the decision maker can justify making investments to adopt or avoid multitasking.
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