Resource constrained project scheduling with uncertain activity durations

Chakrabortty, Ripon K.; Sarker, Ruhul A.; Essam, Daryl

doi:10.1016/j.cie.2016.12.040

Cited by 78 publications

(28 citation statements)

References 44 publications

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“…In Equation 18, completion time intervals of the activities are defined as binary variables. Constraints (15) and (18) also impose non-preemption of the activities.…”

Section: Formulation Of Fully Uncertain Rcpspmentioning

confidence: 99%

An Interval Programming Based Approach for fully uncertain Resource-Constrained Project Scheduling Problem Considering Project Manager’s Attitude toward Risk

Subulan¹

2019

Pamukkale J Eng Sci

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In recent years, there has been a growing attention to model and solve resource-constrained project scheduling problem (RCPSP) under uncertain environments. In most of the real-life cases, project managers may face with many uncertainties in activity durations, resource availabilities, resource requirements of the activities, the earliest and latest finishing times of the activities etc. In addition to these input parameters, project schedule which represents the starting and/or completion times of the activities should also be considered as uncertain variables in such a fully uncertain environments where all of the project data are imprecise. Based on this motivation, this paper presents an interval programming based transformation approach to overcome fully uncertain nature of the problem. In detail, classical discrete-time binary integer programming model of the deterministic problem was extended by incorporating interval-valued parameters and decision variables. Then, fully uncertain RCPSP was transformed into the crisp equivalent form by making use of interval programming, interval ranking and interval arithmetic operations. In the proposed approach, interval arithmetic operations are performed by using supplementary information obtained from the project manager. Thus, the proposed approach is also able to take into account the project managers' attitude toward risk and produces more acceptable and risk-free solutions. Finally, a real-life liquefied natural gas (LNG) storage tank construction project in a petroleum refinery is presented for testing its validity and practicality. The computational results have shown that more applicable and information efficient project schedules can be derived via the proposed approach according to the project manager's attitude toward risk.

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“…In Equation 18, completion time intervals of the activities are defined as binary variables. Constraints (15) and (18) also impose non-preemption of the activities.…”

Section: Formulation Of Fully Uncertain Rcpspmentioning

confidence: 99%

An Interval Programming Based Approach for fully uncertain Resource-Constrained Project Scheduling Problem Considering Project Manager’s Attitude toward Risk

Subulan¹

2019

Pamukkale J Eng Sci

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“…In the second stage, the best schedule is selected from the Pareto optimal solutions based on Monte-Carlo simulation. Depending on different uncertainty characteristics, Chakrabortty et al [33] developed six different heuristics to incorporate the uncertain duration as a deterministic constraint in a robust optimization model, and a Coin-Branch & Cut algorithm was adopted as the solver.…”

Section: Proactive Project Scheduling Undermentioning

confidence: 99%

“…Secondly, in each iteration, one of the five neighborhood operators is selected based on the roulette wheel selection method. After the conduct of the neighborhood operator and evaluation on the solution, the new individual is chosen if the solution quality is improved, and the probabilities of neighborhood selection are updated according to (32) and (33). The iterative process continues until the number of iteration reaches N iter n gs , and the best individual replaces the original one in the teacher group.…”

Section: Complexitymentioning

confidence: 99%

A Proactive Robust Scheduling Method for Aircraft Carrier Flight Deck Operations with Stochastic Durations

Su¹,

Wang²,

et al. 2018

Complexity

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The operations on the aircraft carrier flight deck are carried out in a time-critical and resource-constrained environment with uncertainty, and it is of great significance to optimize the makespan and obtain a robust schedule and resource allocation plan for a greater sortie generation capacity and better operational management of an aircraft carrier. In this paper, a proactive robust optimization method for flight deck scheduling with stochastic operation durations is proposed. Firstly, an operation on node-flow (OONF) network is adopted to model the precedence relationships of multi-aircraft operations, and resource constraints categorized into personnel, support equipment, workstation space, and supply resource are taken into consideration. On this basis, a mathematical model of the robust scheduling problem for flight deck operation (RSPFDO) is established, and the goal is to maximize the probability of completing within the limitative makespan (PCLM) and minimize the weighted sum of expected makespan and variance of makespan (IRM). Then, in terms of proactive planning, both serial and parallel schedule generation schemes for baseline schedule and robust personnel allocation scheme and equipment allocation adjustment scheme for resource allocation are designed. In terms of executing schedules, an RSPFDO-oriented preconstraint scheduling policy (CPC) is proposed. To optimize the baseline schedule and resource allocation, a hybrid teaching-learning-based optimization (HTLBO) algorithm is designed which integrates differential evolution operators, peak crossover operator, and learning-automata-based adaptive variable neighborhood search strategy. Simulation results shows that the HTLBO algorithm outperforms both some other state-of-the-art algorithms for deterministic cases and some existing algorithms for stochastic project scheduling, and the robustness of the flight deck operations can be improved with the proposed resource allocation schemes and CPC policy.

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“…Scheduling involves the allocation of given resources to activities while determining the start and completion times of those associated activities. Due to scarce resources, the allocation of those resources makes the solution process more complex and so several compromises have to be made to solve the RCPSP to the desired level of near‐optimality (Chakrabortty et al., , ).…”

Section: Introductionmentioning

confidence: 99%

Multi‐mode resource‐constrained project scheduling using modified variable neighborhood search heuristic

Chakrabortty

Abbasi

Ryan

2019

Int Trans Operational Res

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This paper aims at providing a fast near‐optimum solution to the multi‐mode resource‐constrained project scheduling problems (MRCPSPs), for projects with activities that have known deterministic renewable and nonrenewable resource requirements. The MRCPSP is known to be nondeterministic polynomial‐time hard and has been solved using various exact, heuristic, and meta‐heuristic procedures. In this paper, a modified variable neighborhood search heuristic algorithm is used as an advanced optimization technique that suits scheduling problems. For the experimental study, we have considered a standard set of 3929 multi‐mode benchmark instances from the project scheduling library with a range of projects comprising 10–30 activities. Moreover, for a better comparison, this research also considers a standard set of 4320 newly developed multi‐mode instances from MMLIB50, MMLIB100, and MMLIB+ datasets. With the limit of 50,000 schedules on these datasets, our proposed algorithm provides better makespan for 106, 34, and 1601 instances, respectively, which justifies the efficiency of the proposed algorithm, particularly for projects with a larger number of activities. The results reported in this paper can be used as a benchmark for other researchers to compare and improve.

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Resource constrained project scheduling with uncertain activity durations

Cited by 78 publications

References 44 publications

An Interval Programming Based Approach for fully uncertain Resource-Constrained Project Scheduling Problem Considering Project Manager’s Attitude toward Risk

An Interval Programming Based Approach for fully uncertain Resource-Constrained Project Scheduling Problem Considering Project Manager’s Attitude toward Risk

A Proactive Robust Scheduling Method for Aircraft Carrier Flight Deck Operations with Stochastic Durations

Multi‐mode resource‐constrained project scheduling using modified variable neighborhood search heuristic

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