An event-based reactive scheduling approach for the Resource Constrained Project Scheduling Problem with unreliable resources

被引:22
作者
Chakrabortty, Ripon K. [1 ]
Rahman, Humyun Fuad [1 ]
Haque, Khan M. A. [2 ]
Paul, Sanjoy Kumar [3 ]
Ryan, Michael J. [1 ]
机构
[1] UNSW Canberra, Sch Engn & IT, Capabil Syst Ctr, ADFA, Canberra, ACT, Australia
[2] Univ Texas Arlington, Dept Ind Mfg & Syst Engn, Arlington, TX 76019 USA
[3] Univ Technol Sydney, UTS Business Sch, Sydney, NSW, Australia
关键词
Resource Constrained Project Scheduling; Event-based rescheduling; Disruptions; Mixed integer linear programming; Enhanced iterated greedy; Meta-heuristic approach; CONTINUOUS-TIME; MILP FORMULATION; BOUND ALGORITHM; STRATEGIES; DISCRETE; MODELS; FRAMEWORK;
D O I
10.1016/j.cie.2020.106981
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The Resource Constrained Project Scheduling Problem (RCPSP) is a combinatorial optimization problem which is non-deterministic polynomial-time (NP)-hard in nature. Due to the diversified applications of RCPSPs, they have been commonly used as scheduling procedures in real-world problems. Since, in practice, project data are prone to changes or disruptions, this paper introduces a mathematical model for a reactive scheduling approach, called the Event Based Reactive Approach (EBRA). This proposed EBRA approach is employed to examine its recovery performance under both a single disruption and a series of independent resource disruptions. Several simulated disruption data are hypothesized to represent real-world disruption scenarios and, without loss of generality, the proposed reactive approach is proved to be efficient in reducing the number of variables and computational complexity and also to be resilient in realistic changes, such as duration inflation and dynamic resource usages. Along with employing an exact method by LINGO software, this paper also proposes an enhanced iterated greedy (EnIG) approach to meta-heuristically solve larger and computationally expensive benchmark instances taken from the Project Scheduling Library (PSPLIB).
引用
收藏
页数:16
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