Critical Chain Scheduling and Buffer Management (CC/BM) has shown to provide an effective approach for building robust project schedules and to offer a valuable control tool for coping with schedule variability. Yet, the current buffer monitoring mechanism faces a problem of neglecting the dynamic feature of the project execution and related activity information when taking corrective actions. The schedule risk analysis (SRA) method in a traditional PERT framework, on the other hand, provides important information about the relative activity criticality in relation to the project duration which can highlight management focus. It is implied, however, that control actions are independent from the current project schedule performance. This paper attempts to research these defects of both tracking methods and proposes a new project schedule monitoring framework by introducing the activity cruciality index as a trigger for effective expediting to be integrated into the buffer monitoring process. Furthermore, dynamic action threshold settings that depend on the project progress as well as the buffer penetration are presented and examined in order to exhibit a more accurate control system. Our computational experiment demonstrates the relative dominance of the integrated schedule monitoring methods compared to the predominant buffer management approach in generating better control actions with less effort and an increased tracking efficiency, especially when the increasing buffer trigger point is combined with decreasing sensitivity action threshold values.
The rapidly changing marketplace together with the increasing complexity of contemporary projects makes it more likely that project activities will have uncertain durations, incurring a generally low probability of on-time delivery. Thus, project control that aims to track the project performance and to expedite relevant activities when necessary has become the main aspect within the scope of project management in order to ensure a successful scheduling outcome. The Critical Chain Scheduling and Buffer Management (CC/BM) has shown to provide a popular approach to build robust project schedules and to offer a valuable control tool for coping with schedule variability. However, the most current buffer management (BM) practice faces a problem of neglecting the cost information when taking expediting actions. In view of this defect, we introduce a new control procedure on the basis of CC/BM that evaluates the probability of successful project completion relative to the cost of crashing and that determines when to expedite which activities in a cost-effective manner. Results of an experimental application of the proposed method present its relative dominance over the currently widely adopted BM approach with respect to project time and cost performance.
In recent years, gray markets have become a significant phenomenon in the business practice. This paper investigates the gray markets issues in differentiated duopoly case by considering quantity competition among firms. We develop a game-theoretic model and provide equilibrium results for three scenarios, i.e. the benchmark scenario 'no gray market', the scenario 'parallel imports act as a buffer against a follower's product' and the scenario 'gray markets stimulate the competition'. By the analysis of the equilibrium results, some important managerial insights are obtained. Finally, by comparison of the equilibrium results among different scenarios, we study the impact of gray markets on manufacturers' optimal strategies and profits in differentiated duopoly.
This study investigates the robust resource-constrained max-NPV project problem with stochastic activity duration. First, the project net present value (NPV) and the expected penalty cost (EPC) are proposed to measure quality robustness and solution robustness from the perspective of discounted cash flows, respectively. Then, a composite robust scheduling model is proposed in the presence of activity duration variability and a two-stage algorithm that integrates simulated annealing and tabu search is developed to deal with the problem. Finally, an extensive computational experiment demonstrates the superiority of the combination between quality robustness and solution robustness as well as the effectiveness of the proposed two-stage algorithm for generating project schedules compablack with three other algorithms, namely, simulated annealing, tabu search, and multi-start iterative improvement method.Computational results indicate that the proactive project schedules with composite robustness not only can effectively protect the payment plan from disruptions through allocating appropriate time buffers, but also can achieve a remarkable performance with respect to the project NPV.
The critical chain scheduling and buffer management (CC/BM) methodology has proven to be a favorable approach to schedule resource-constrained projects and to offer a valuable control tool for monitoring projects under uncertainty. The previous studies on CC/BM seem to have neglected the cost performance, which might render its wider applications to the modern economic activities that are mostly performed in a project way. This paper presents an improved CC/BM framework that allows additional resource allocation/reallocation to bring forward activity starting times based on cost and schedule stability criteria. In the planning phase, the decision is made concerning the regular resource availability period in order to minimize the expected resource costs. In the execution phase, a scheduled order repair method for rescheduling along with two reactive resource allocation procedures as the corrective action whenever delays are beyond a certain buffer threshold are presented and examined in order to exhibit a comprehensive project schedule/cost control system that is adaptive to the CC/BM management logic. Finally, our computational experiment demonstrates the benefits of the proposed reactive methods under different cost or availability parameters.
In the recent decades, the recognition that uncertainty lies at the heart of modern project management has induced considerable research efforts on robust project scheduling for dealing with uncertainty in a scheduling environment. The literature generally provides two main strategies for the development of a robust predictive project schedule, namely robust resource allocation and time buffering. Yet, the previous studies seem to have neglected the potential benefits of an integration between the two. Besides, few efforts have been made to protect simultaneously the project due date and the activity start times against disruptions during execution, which is desperately demanded in practice. In this paper, we aim at constructing a proactive schedule that is not only short in time but also less vulnerable to disruptions. Firstly, a bi-objective optimization model with a proper normalization of the two components is proposed in the presence of activity duration variability. Then a two-stage heuristic algorithm is developed which deals with a robust resource allocation problem in the first stage and optimally determines the position and the size of time buffers using a simulated annealing algorithm in the second stage. Finally, an extensive computational experiment on the PSPLIB network instances demonstrates the superiority of the combination between resource allocation and time buffering as well as the effectiveness of the proposed two-stage algorithm for generating proactive project schedules with composite robustness.
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