Quality- and profit-oriented scheduling of resource-constrained projects with flexible project structure via a genetic algorithm

Kellenbrink, Carolin; Helber, Stefan

doi:10.1504/ejie.2016.078807

Cited by 11 publications

(4 citation statements)

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“…Project scheduling problems are aimed at optimizing the activity execution sequence through the optimum allocation of resources to activities. Project scheduling problems are further classified as either Resource-Constrained Project Scheduling Problems (RCPSP) with the objective of minimizing makespan [76,77,78,79,80,81,82,83,84,85,86,87] or Time-Constrained Project Scheduling Problems (TCPSP) aimed at minimizing resource requirements [88,89,90,91,92]. Extensive literature has been reported on mathematical programming approaches and metaheuristics such as evolutionary algorithms and simulated annealing on modeling and solving project scheduling problems [93,94,95].…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Sequencing and Scheduling Optimization in Low-Volume Low-Variety Production Systems

Russell¹

2022

Preprint

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<p>Despite prominent scholarly advancements in scheduling optimization approaches for a wide range of production systems, limited research has been reported on sequencing and scheduling optimization strategies in Low-Volume Low-Variety production systems. This dissertation fills the gap in the current literature through the formulation and the proposal of a suite of mathematical programming models and heuristic algorithms, capturing the unique characteristics and constraints inherent in such production systems. In the first section of this dissertation a suite of mixed-integer multi-objective linear mathematical programming models are proposed for solving discrete-time single work center scheduling problems, distinguished by a key decision criterion of permitting or prohibiting the traveling of incomplete activities. It was evident through personal observations however, that there exist scenarios where resources are shared between parallel work centers, which yielded to further research in the use of shared resource pools in multi-parallel work center scheduling problems. A novel suite of mathematical programming models are proposed for solving single and multi-parallel work center scheduling problems with shared or dedicated resources. The mathematical programming models formulated in this section are modular, signifying that constraints can be added or removed without jeopardizing the integrity of the mathematical models. The proposed optimization models were validated and verified through a real-world case study where significant cost savings in form of resource requirements are realized through the integration of shared resource pools. It is often the case however, that activity processing times and planning horizon are not discrete. To tackle continuous-time work center scheduling problems a novel suite of mathematical programming models is formulated and proposed in the final section of this dissertation, as well as two new genetic algorithms for solving large-scale scheduling problems. The proposed mathematical programming models and metaheuristics are aimed at optimizing the production schedule as well as activity execution sequence to minimize overall cost and resource requirements. The optimization models proposed through this dissertation are validated and verified through a real-world case study of the final assembly line of a narrow body private aircraft, where the problems were solved to optimality.</p>

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Section: Background and Literature Reviewmentioning

confidence: 99%

Sequencing and Scheduling Optimization in Low-Volume Low-Variety Production Systems

Russell¹

2022

Preprint

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“…Aircraft engine remanufacturing is executed by independent service contractors or original equipment manufacturers. In either case, this complex process typically has a project character, see Kellenbrink and Helber (2015) and Kellenbrink and Helber (2016), as the state of the engines as well as the chosen repair or replace options differ from case to case. The customers are typically airlines that are interested in short remanufacturing processes.…”

Section: Projects With Flexible Capacity Constraints Makespan-dependmentioning

confidence: 99%

Profit-oriented scheduling of resource-constrained projects with flexible capacity constraints

Schnabel

Kellenbrink

Helber

2018

Bus Res

Self Cite

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We consider a novel generalization of the resource-constrained project scheduling problem (RCPSP). Unlike many established approaches for the RCPSP that aim to minimize the makespan of the project for given static capacity constraints, we consider the important real-life aspect that capacity constraints can often be systematically modified by temporarily assigning costly additional production resources or using overtime. We, furthermore, assume that the revenue of the project decreases as its makespan increases and try to find a schedule with a profitmaximizing makespan. Like the RCPSP, the problem is NP-hard, but unlike the RCPSP, it turns out that an optimal schedule does not have to be among the set of so-called active schedules. Scheduling such a project is a formidable task, both from a practical and a theoretical perspective. We develop, describe, and evaluate alternative solution encodings and schedule decoding mechanisms to solve this problem within a genetic algorithm framework and we compare the solutions obtained to both optimal reference values and the results of a commercial local search solver called LocalSolver.

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“…In the future, research can explore the possibility of integrating other knowledge areas including risk management and procurement management with the development of the project schedule. Meta-heuristics models were also proposed for scheduling multiple-resource constrained project scheduling problems [16][17][18][19][20]. Fuzzy models [21][22][23] also studied the problem of resource allocation under uncertain conditions.…”

Section: Introductionmentioning

confidence: 99%

Scheduling Multi-Mode Resource-Constrained Projects Using Heuristic Rules Under Uncertainty Environment

Abdel‐Basset¹,

Sleem²,

Atef³

et al. 2022

Computers, Materials &Amp; Continua

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Project scheduling is a key objective of many models and is the proposed method for project planning and management. Project scheduling problems depend on precedence relationships and resource constraints, in addition to some other limitations for achieving a subset of goals. Project scheduling problems are dependent on many limitations, including limitations of precedence relationships, resource constraints, and some other limitations for achieving a subset of goals. Deterministic project scheduling models consider all information about the scheduling problem such as activity durations and precedence relationships information resources available and required, which are known and stable during the implementation process. The concept of deterministic project scheduling conflicts with real situations, in which in many cases, some data on the activity' s durations of the project and the degree of availability of resources change or may have different modes and strategies during the process of project implementation for dealing with multi-mode conditions surrounded by projects and their activity durations. Scheduling the multi-mode resource-constrained project problem is an optimization problem whose minimum project duration subject to the availability of resources is of particular interest to us. We use the multi-mode resource allocation and scheduling model that takes into account the dynamicity features of all parameters, that is, the scheduling process must be flexible to dynamic environment features. In this paper, we propose five priority heuristic rules for scheduling multi-mode resource-constrained projects under dynamicity features for more realistic situations, in which we apply the proposed heuristic rules (PHR) for scheduling multi-mode resource-constrained projects. Five projects are considered test problems for the PHR. The obtained results rendered by these priority rules for the test problems are compared by the results obtained from 10 well-known heuristics rules rendered for the same test problems. The results in many cases of the proposed priority rules are very promising, where they achieve better scheduling dates in many test case problems and the same results

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Quality- and profit-oriented scheduling of resource-constrained projects with flexible project structure via a genetic algorithm

Cited by 11 publications

References 0 publications

Sequencing and Scheduling Optimization in Low-Volume Low-Variety Production Systems

Sequencing and Scheduling Optimization in Low-Volume Low-Variety Production Systems

Profit-oriented scheduling of resource-constrained projects with flexible capacity constraints

Scheduling Multi-Mode Resource-Constrained Projects Using Heuristic Rules Under Uncertainty Environment

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