On top of that, the effects of CW on firms’ productivity are incorporated into our long-run analysis. Firstly, the short-run daily and periodic commute patterns of employees are investigated in a modified activity-based bottleneck model. A bi-level economic model encapsulating employers’ and employees’ choices on their work schedule is then developed. Without policy intervention, how many firms will choose CW? Is it socially beneficial to encourage all commuters to switch to CW? This paper mainly addresses these questions.

In the literature, it has been clearly demonstrated that CW can significantly reduce commuting trips per pay period and thereby relieve peak hour congestion. The numerical results demonstrate that implementing the proposed optimal staggered work schedules strategy accounting for commuters’ departure trip time choice can significantly reduce the traffic congestion in urban networks.Ĭompressed work schedule (CW) is one of the widely known flexible work hours arrangements (FWAs). We assess the accuracy and effectiveness of the proposed method using an individual-level trip-based macroscopic simulation model. We solve the optimization problem for a test network and analyze the sensitivity of the Pareto solution to the policy parameters of the model. The time-varying congestion dynamics are modeled using macroscopic fundamental diagrams. We formulate the optimal work schedule problem in a bicentric network as a multi-objective optimization program that simultaneously minimizes the total travel time and the schedule deviation for the firms while satisfying near-equilibrium temporal conditions.

The objective is to optimize the work start times of individual firms with minimum deviations from their initial schedules while taking into account that commuters choose their departure time selfishly to minimize their travel cost. In this paper, we propose an optimal staggered work schedules problem to minimize the network total travel time and prevent the schedule delay in the trips of commuters over morning peaks in a bicentric network. In urban networks, traffic congestion can be curbed by deconcentrating the temporal distribution of the travel demand. In this paper, a case study of Traffic Pattern is gauged Needs to be framed and verified once the individual task isĪpplied. Objectives are branded into sub goals based on theįunctionality allied within the object. Outlines the state and behavior of a thing directly related with the The knowledge depiction techniquesĭemonstrate the problem from objected oriented viewpoint which

The assertions improve the intelligibility inĪccepting the prediction of traffic occurrence under different age TheĬharacterized knowledge is taken to derive finest assertions usingĪND-OR-graphs. Highlight the density associated with each object. The semantic net representation and inferences are used to Paper, the issues involved in traffic consequences are analyzed. Information in order to reduce real world complexity. Techniques are almost used in every field to retrieve the hidden In order to spring innovative information. Known and applied method for scrutinizing huge set of database The Knowledge representation is the extensively In terms of total net benefit, while work schedule agglomeration of all commuters leads to the maximum in some cases, the polarized agglomeration of the two heterogenous groups can never achieve the optimum. For total commuting cost, it is found that the rigid school schedule for households may impede the benefits of flextime in commuting cost saving. Further, we analyze optimal schedule choices with two system performance indicators. If flextime is not flexible enough, commuters tend to agglomerate in work schedule choice at long-run equilibrium. Both short-run travel behaviours and long-run work start time selection of heterogenous commuters are examined under agglomeration economies. On this account, we incorporate household travels into the work starting time choice model in this study. In fact, as one of the main reasons to adopt flextime, household travel plays an influential role in travelers' decision making on work schedule selection. Yet, most analytical studies assume the single trip purpose in peak hours (to work) only and do not consider the household travels (daycare drop-off/pick-up). Previous literature has developed bi-level models of the work starting time choice considering both labor output and urban mobility. Flextime is one of the efficient approaches in travel demand management to reduce peak hour congestion and encourage social distancing in epidemic prevention.

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