A Fuzzy Ant Colony Approach to Fully Fuzzy Resource Constrained Project Scheduling Problem

Yousefli, Amir

doi:10.7232/iems.2017.16.3.307

Cited by 10 publications

(8 citation statements)

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“…Knyazeva et al [38] also provided an uncertain project schedule including fuzzy starting and finishing times for a GIS software development project activities under resource allocation and uncertainty. Yousefli [39] proposed a fully fuzzy mathematical programming model for a RCPSP by considering the fuzzy scheduling concept. In detail, they calculated the activity schedule (starting and finishing times) as fuzzy numbers because of the uncertainty of all the project parameters.…”

Section: Related Literaturementioning

confidence: 99%

“…Otherwise, risky solutions which contain overlaps of the interval numbers are produced when the risk parameter ( ) is equal to "1". The resource availability constraint (27) can be transformed into the crisp equivalent form as in Equations (38)- (39). Similar to the Equations (32)- (33), the transformation of the resource availability constraint is carried out under uncertain equality relations between the base variables of interval numbers.…”

Section: The Proposed Transformation Approachmentioning

confidence: 99%

“…To satisfy this condition, an interval ranking method can also be utilized. But, this makes the mathematical model of the stated problem highly non-linear as in the study of Yousefli [39]. When the risk parameter ( ) of the project manager is equal to "0", risk-free solutions resulting from standard interval arithmetic can be yielded.…”

Section: The Proposed Transformation Approachmentioning

confidence: 99%

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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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Section: Related Literaturementioning

confidence: 99%

Section: The Proposed Transformation Approachmentioning

confidence: 99%

Section: The Proposed Transformation Approachmentioning

confidence: 99%

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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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“…Fuellerer et al [39] studied the two-dimensional loadingvehicle routing problem and the proposed ACO algorithm based on the AS. Yousefli [40] developed the fuzzy AC approach to consider the project scheduling problem. Tchoupo et al [41] developed a meta-heuristic based on the ACO combined with dedicated local search algorithms for the PDPTW.…”

Section: Introductionmentioning

confidence: 99%

Vehicle Routing Problem Considering Reconnaissance and Transportation

Kim

Moon

2021

Sustainability

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Troop movement involves transporting military personnel from one location to another using available means. To minimize damage from enemies, the military simultaneously uses reconnaissance and transportation units during troop movements. This paper proposes a vehicle routing problem considering reconnaissance and transportation (VRPCRT) for wartime troop movements. The VRPCRT is formulated as a mixed-integer programming model for minimizing the completion time of wartime troop movements and reconnaissance, and transportation vehicle routes were determined simultaneously in the VRPCRT. For this paper, an ant colony optimization (ACO) algorithm for the VRPCRT was also developed, and computational experiments were conducted to compare the ACO algorithm’s performance and that of the mixed-integer programming model. The performance of the ACO algorithm was shown to yield excellent results even for the real-size problem. Furthermore, a sensitivity analysis of the change in the number of reconnaissance and transportation vehicles was performed, and the effects of each type of vehicle on troop movement were analyzed.

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“…They proposed a multi objective nonlinear mathematical model and an algorithm for solving the problem. Some of the other recent papers in the literature are conducted by Castro-Lacouture et al [25], Afshar and Fathi [26], Shi and Gong [27], Wang and Huang [28] , Bhaskar et al [29], Ponz-Tienda et al [30], Maravas and Pantouvakis [31], Xu and Zhang [32], Masmoudi and Haït [33], Huang et al [34] , Chrysafis and Papadopoulos [35], Huang et al [36], Yu et al [37], Yousefli [38], Zohoori et al [39], Habibi et al [40] Alipouri et al [41] and Birjandi and Mousavi [42]. As seen from the literature review of this paper, fuzzy project scheduling problems have been mostly investigated with fuzzy ranking methods, fuzzy simulation, and heuristic or metaheuristic.…”

Section: Introductionmentioning

confidence: 99%

Credibility based chance constrained programming for project scheduling with fuzzy activity durations

Arık

2019

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

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This paper proposes a credibility based chance constrained programming approach for project scheduling problems with fuzzy activity durations where the objective is to minimize the fuzzy project completion time. This paper expresses the fuzzy events such as a project activity’s duration or project completion time with fuzzy chance constraints and the chance of a fuzzy event is illustrated with fuzzy credibility distribution. Due to uncertainty in durations of a project, fuzzy sets and fuzzy numbers can be used in order to illustrate the uncertainty and find a solution space for the problem. Therefore, fuzzy credibility based chance constraint technique is investigated for project scheduling problems with fuzzy activity durations considering the uncertainty or chance of a fuzzy event within a closed interval. In this paper, a fuzzy mathematical model and its crisp equivalent by using credibility measure and chance-constrained programming are given for project scheduling problems with fuzzy activity durations.

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A Fuzzy Ant Colony Approach to Fully Fuzzy Resource Constrained Project Scheduling Problem

Cited by 10 publications

References 0 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

Vehicle Routing Problem Considering Reconnaissance and Transportation

Credibility based chance constrained programming for project scheduling with fuzzy activity durations

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