Bi-objective resource-constrained project scheduling with robustness and makespan criteria

Abbasi, Babak; Shadrokh, Shahram; Arkat, Jamal

doi:10.1016/j.amc.2005.11.160

Cited by 86 publications

(47 citation statements)

References 7 publications

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“…Table 4 presents the results from the paper by Abbasi et al [10]. They used LRS to calculate the time of activities.…”

Section: Population Size=50mentioning

confidence: 99%

“…Constraint (8) show that project starts at zero time and constraint (9) calculates the latest start time of each activity. Constraint (10) calculates the earliest time of each activity. Constraint (11) before Eq.…”

Section: The Modelmentioning

confidence: 99%

“…The model was then solved using multi objective tabu search (MOTS). In the following year, Abbasi et al [10] solved the same problem using simulate annealing (SA) based approach. Aligned with those papers, in this paper, a single renewable resource and biobjective model is considered and addressed using differential evolution (DE) algorithm [11].…”

Section: Introductionmentioning

confidence: 99%

“…This paper is developed based on two papers by Al-Fawzan and Haouari [3] and Abbasi et al [10]. Al-Fawzan and Haouari [3] proposed a bi-objective model in which two significant objectives were taken into account: 'makespan minimizing' and 'robustness maximizing'.…”

Section: Introductionmentioning

confidence: 99%

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A Robust Solution to Resource-Constraint Project Scheduling Problem

Mahalleh

Ashjari

Yousefi

et al. 2017

IJFIS

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This paper aims to propose a solution to the resource-constraint project scheduling problem (RCPSP). RCPSP is a significant scheduling problem in project management. Currently, there are insufficient studies dealing with the robustness of RCPSP. This paper improves the robustness of RCPSP and develops a Robust RCPSP, namely RRCSP. RRCSP is structured with relaxing a fundamental assumption that is 'the tasks start on time as planned'. Relaxing this assumption makes the model more realistic. The proposed solution minimizes the makespan while maximizing the robustness. Maximizing the robustness requires maximizing floating time of activities (it is NP hard). This creates more stability in the project finishing time. RCPSP stands as the root cause of many other problems such as multi-mode resourceconstrained project scheduling problems (MRCPSP), multi-skill resource-constrained project scheduling problem (MSRCPSP), or similar problems and hence proposing a solution to this problem contributes to pave a new line for future research in other mentioned areas. The applicability of the proposed model is examined through a numerical example.

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“…Table 4 presents the results from the paper by Abbasi et al [10]. They used LRS to calculate the time of activities.…”

Section: Population Size=50mentioning

confidence: 99%

Section: The Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Robust Solution to Resource-Constraint Project Scheduling Problem

Mahalleh

Ashjari

Yousefi

et al. 2017

IJFIS

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“…The proposed approach worked based on using genetic operators with fuzzy logic controller (FLC) through initializing the revised serial method with precedence and resources constraints. Afterward, an attempt has been accomplished for minimizing , as well as maximizing solution robustness by increasing float time maximization (Abbasi et al, 2006). In another study, a two-stage algorithm was developed for RCPSP while minimize , considered as an acceptance threshold for the second stage and then, in next stage, a set of 12 alternative robust predictive indicators was employed to maximize robustness of the project (Chtourou & Haouari, 2008).…”

Section: Introductionmentioning

confidence: 99%

Minimizing makespan of a resource-constrained scheduling problem: A hybrid greedy and genetic algorithms

Delgoshaei¹,

Ariffin²,

Baharudin³

et al. 2015

10.5267/j.ijiec

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Resource-Constrained Project Scheduling Problem (RCPSP) is considered as an important project scheduling problem. However, increasing dimensions of a project, whether in number of activities or resource availability, cause unused resources through the planning horizon. Such phenomena may increase makespan of a project and also decline resource-usage efficiency. To solve this problem, many methods have been proposed before. In this article, an effective backward-forward search method (BFSM) is proposed using Greedy algorithm that is employed as a part of a hybrid with a two-stage genetic algorithm (BFSM-GA). The proposed method is explained using some related examples from literature and the results are then compared with a forward serial programming method. In addition, the performance of the proposed method is measured using a mathematical metric. Our findings show that the proposed approach can provide schedules with good quality for both small and large scale problems.

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Task management on fully heterogeneous micro‐server system: Modeling and resolution strategies

Zaourar

Ait

Philippe

2018

Concurrency and Computation

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Summary Many of today's important applications of our everyday lives, eg, weather forecast, design of plane and car shapes, medical analysis, or search engine queries depend on massively parallel computer programs executed in data centers. A large amount of energy is used to power them, and it is of primary importance to compute more efficiently to sustain the increasing demand of computing power while keeping energy consumption reasonable. One promising research path in this domain is heterogeneous systems since specific computing resources (processors, accelerators, etc) are more adapted to efficiently execute parts of applications. Nevertheless, the exploitation of these platforms raises new challenges in terms of application management optimization. The aim of our work is to determine effective algorithms to exploit these heterogeneous platforms by finding appropriate application mapping and scheduling to optimize the execution time and energy consumption with respect to various constraints. To achieve this goal, there is a need of a detailed modeling of the applications and the underlying hardware to be able to find realistic solutions. In this paper, we propose such a model, provide two implementations with state‐of‐the‐art tools, and propose a fast greedy online resolution algorithm and preliminary mapping and scheduling numerical results.

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Bi-objective resource-constrained project scheduling with robustness and makespan criteria

Cited by 86 publications

References 7 publications

A Robust Solution to Resource-Constraint Project Scheduling Problem

A Robust Solution to Resource-Constraint Project Scheduling Problem

Minimizing makespan of a resource-constrained scheduling problem: A hybrid greedy and genetic algorithms

Task management on fully heterogeneous micro‐server system: Modeling and resolution strategies

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