A queueing model for managing small projects under uncertainties

Abstract

a b s t r a c tWe consider a situation in which a home improvement project contractor has a team of regular crew members who receive compensation even when they are idle. Because both projects arrivals and the completion time of each project are uncertain, the contractor needs to manage the utilization of his crews carefully. One common approach adopted by many home improvement contractors is to accept multiple projects to keep his crew members busy working on projects to generate positive cash flows. However, this approach has a major drawback because it causes "intentional" (or foreseeable) project delays. Intentional project delays can inflict explicit and implicit costs on the contractor when frustrating customers abandon their projects and/or file complaints or lawsuits. In this paper, we present a queueing model to capture uncertain customer (or project) arrivals and departures, along with the possibility of customer abandonment. Also, associated with each admission policy (i.e., the maximum number of projects that the contractor will accept), we model the underlying tradeoff between accepting too many projects (that can increase customer dissatisfaction) and accepting too few projects (that can reduce crew utilization). We examine this tradeoff analytically so as to determine the optimal admission policy and the optimal number of crew members. We further apply our model to analyze other issues including worker productivity and project pricing. Finally, our model can be extended to allow for multiple classes of projects with different types of crew members.

A multi-station system for reducing congestion in high-variability queues

“…Finally, and with the spirit of expanding the applications of the service allocation scheme considered in this paper, one may look at project management. For example, an interesting recent work on applying queueing theory for project selection and resource allocation in home improvement is byBai et al (2016). Several extensions and refinements of the work inBai et al (2016) are possible with task allocation schemes similar the one in this paper.…”

Industrial big data–based scheduling modeling framework for complex manufacturing system

“…4 In queueing theory, workpieces are waiting to be processed in front of machines; the waiting sequences are determined by workpiece priorities; the workpiece arrival and processing time should follow certain assumptions. 5 The figure below shows how queueing theory works (Figure 1). Once a queueing model is established, the optimization target like makespan can be easily derived by optimization methods while meeting all the constraints.…”

A reconfigurable model for implementation in the closing phase of a wind turbines project construction

“…Bittencourt et al (2018) focused on the contributions of queuing theory to hospital capacity management to improve organizational performance and deal with increased demand in the healthcare sector. Bai et al (2016) presented a queuing model to keep uncertain customers and deal with project arrivals and departures by considering the possibility of customer abandonment. Campello et al (2016) proposed a stochastic model of a baseline case-manager system, formulated models that provide performance bounds and stability conditions for the baseline system, and developed two approximations, one of which was based on a two-time-scale approach.…”