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Fairness in optimizing bus-crew scheduling process.

ABSTRACT: This work proposes a model considering fairness in the problem of crew scheduling for bus drivers (CSP-BD) using a hybrid ant-colony optimization (HACO) algorithm to solve it. The main contributions of this work are the following: (a) a valid approach for cases with a special cost structure and constraints considering the fairness of working time and idle time; (b) an improved algorithm incorporating Gamma heuristic function and selecting rules. The relationships of each cost are examined with ten bus lines collected from the Beijing Public Transport Holdings (Group) Co., Ltd., one of the largest bus transit companies in the world. It shows that unfair cost is indirectly related to common cost, fixed cost and extra cost and also the unfair cost approaches to common and fixed cost when its coefficient is twice of common cost coefficient. Furthermore, the longest time for the tested bus line with 1108 pieces, 74 blocks is less than 30 minutes. The results indicate that the HACO-based algorithm can be a feasible and efficient optimization technique for CSP-BD, especially with large scale problems.

SUBMITTER: Ma J

PROVIDER: S-EPMC5708815 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Fairness in optimizing bus-crew scheduling process.

Ma Jihui J Song Cuiying C Ceder Avishai Avi AA Liu Tao T Guan Wei W

PloS one 20171130 11

This work proposes a model considering fairness in the problem of crew scheduling for bus drivers (CSP-BD) using a hybrid ant-colony optimization (HACO) algorithm to solve it. The main contributions of this work are the following: (a) a valid approach for cases with a special cost structure and constraints considering the fairness of working time and idle time; (b) an improved algorithm incorporating Gamma heuristic function and selecting rules. The relationships of each cost are examined with t ...[more]

PMID: 29190772

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Project description:IntroductionThe COVID 19 pandemic increased the need for rapid and accurate diagnostic testing for COVID. When testing became available, a systems response was needed to efficiently accommodate the high-volume flow of patients who needed testing. Self-scheduling of COVID testing was developed to help patients safely and efficiently schedule their COVID testing online or with a mobile app.MethodsWe captured the counts of COVID test appointments, time patients spent in scheduling COVID test appointments, appointment lead times, and no-shows for COVID test appointments. For 17 months of self-scheduling, we retrospectively compared self-scheduling with the concurrent staff scheduling of COVID tests.ResultsFrom November 2020 through March 2022 there were 619 104 scheduled appointments for COVID testing with 22% (136 252) being self-scheduled. For asymptomatic self-scheduled COVID tests, accounting for 10.3% (63 605/619 104) of total COVID tests scheduled, median time to self-schedule was 3.1 min, interquartile range (IQR) [2.4,4.7]. For symptomatic self-schedulers accounting for 11.7% (72 647/619 104) of total COVID tests scheduled, the median time to self-triage and self-schedule was 5.8 min, IQR[4.3,8.9]. Self-scheduled COVID appointments increased to 44% (42 387/97 086) of the total COVID appointments during the peak month of January 2022. Median appointment lead time for symptomatic self-scheduled COVID test appointments was 6.6 h compared to 2.9 h (P < .0001) for symptomatic staff scheduled appointments. However, adjusting for the 24% (32 194/135 252) that self-scheduled during hours when testing was unavailable, the median appointment lead time for symptomatic self-scheduled patients dropped to 3.6 h. No-shows were 2.5% for self-scheduled appointments compared to 3.0% no-shows that were staff scheduled (odds ratio 0.83, P < .0001).ConclusionCOVID testing was self-scheduled for a large percent of scheduled COVID tests, taking patients only a few minutes to complete. Self-scheduling use increased over time, associated with a decreasing use of staff scheduled appointments and lower no-shows.

Project description:Daniels, Porteny and Urrutia et al make a good case for the idea that that public decisions ought to be made not only "in the light of" evidence but also "on the basis of" budget impact, financial protection and equity. Health technology assessment (HTA) should, they say, be accordingly expanded to consider matters additional to safety and cost-effectiveness. They also complain that most HTA reports fail to develop ethical arguments and generally do not even mention ethical issues. This comment argues that some of these defects are more apparent than real and are not inherent in HTA - as distinct from being common characteristics found in poorly conducted HTAs. More generally, HTA does not need "extension" since (1) ethical issues are already embedded in HTA processes, not least in their scoping phases, and (2) HTA processes are already sufficiently flexible to accommodate evidence about a wide range of factors, and will not need fundamental change in order to accommodate the new forms of decision-relevant evidence about distributional impact and financial protection that are now starting to emerge. HTA and related techniques are there to support decision-makers who have authority to make decisions. Analysts like us are there to support and advise them (and not to assume the responsibilities for which they, and not we, are accountable). The required quality in HTA then becomes its effectiveness as a means of addressing the issues of concern to decision-makers. What is also required is adherence by competent analysts to a standard template of good analytical practice. The competencies include not merely those of the usual disciplines (particularly biostatistics, cognitive psychology, health economics, epidemiology, and ethics) but also the imaginative and interpersonal skills for exploring the "real" question behind the decision-maker's brief (actual or postulated) and eliciting the social values that necessarily pervade the entire analysis. The product of such exploration defines the authoritative scope of an HTA.

Dataset Information

Fairness in optimizing bus-crew scheduling process.

Publications

Fairness in optimizing bus-crew scheduling process.

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