scholarly journals Resource-constrained Time-cost-quality-energy-environment Tradeoff in Project Scheduling by Considering Blockchain Technology: A Case Study of Healthcare Project

2021 ◽  
Author(s):  
Reza Lotfi ◽  
Bahareh Kargar ◽  
Alireza Gharehbaghi ◽  
Hanif Hazrati ◽  
Sima Nazari ◽  
...  
Keyword(s):  
Confidence Level ◽  
Project Scheduling ◽  
Conditional Value At Risk ◽  
Time Cost ◽  
Resource Constrained ◽  
Worst Case ◽  
Finish Time ◽  
Blockchain Technology ◽  
Energy Environment

Abstract Blockchain Technology (BCT) is expanding day by day and is used in all pillars of life and projects. In this research, we survey applicable of BCT in project management for the first time. We presented a Resource-Constrained Time-Cost-Quality-Energy-Environment tradeoff problem in project scheduling by considering BCT (RCTCQEEBCT). We utilize hybrid robust stochastic programming, worst case and Conditional Value at Risk (CVaR) to cope with uncertainty and risks. This type of robustification and risk-averse is presented in this research. A real case study is presented in a healthcare project. We utilize GAMS-CPLEX to solve the model. Finally, we analyze finish time, conservative coefficient, the confidence level of CVaR and the number of scenarios. The most important research result is that applying BCT decreases cost, energy, and pollution and increases quality. Moreover, the total gap between RCTCQEEBCT and without BCT is approximately 2.6%. When compacting finish time happens or if the conservative coefficient increases to 100%, costs, energy, and pollution environment increase, but quality decreases. If the confidence level of CVaR increase, the cost, energy and environment function functions grow up and quality is approximately not changed.

Optimizing time, cost and quality in multi-mode resource-constrained project scheduling

2019 ◽  
Vol 9 (1) ◽  
pp. 44-63 ◽  
Author(s):  
Marimuthu Kannimuthu ◽  
Benny Raphael ◽  
Ekambaram Palaneeswaran ◽  
Ananthanarayanan Kuppuswamy
Keyword(s):  
Project Scheduling ◽  
Construction Projects ◽  
Time Cost ◽  
Multi Objective Optimization ◽  
Resource Constrained ◽  
Content Type ◽  
Resource Constrained Project Scheduling ◽  
Multi Objective ◽  
Multi Mode

Purpose The purpose of this paper is to develop a framework to optimize time, cost and quality in a multi-mode resource-constrained project scheduling environment. Design/methodology/approach A case study approach identified the activity execution modes in building construction projects in India to support multi-mode resource-constrained project scheduling. The data required to compute time, cost and quality of each activity are compiled from real construction projects. A binary integer-programming model has been developed to perform multi-objective optimization and identify Pareto optimal solutions. The RR-PARETO3 algorithm was used to identify the best compromise trade-off solutions. The effectiveness of the proposed framework is demonstrated through sample case study projects. Findings Results show that good compromise solutions are obtained through multi-objective optimization of time, cost and quality. Research limitations/implications Case study data sets were collected only from eight building construction projects in India. Practical implications It is feasible to adopt multi-objective optimization in practical construction projects using time, cost and quality as the objectives; Pareto surfaces help to quantify relationships among time, cost and quality. It is shown that cost can be reduced by increasing the duration, and quality can be improved only by increasing the cost. Originality/value The use of different activity execution modes compiled from multiple projects in optimization is illustrated, and good compromise solutions for the multi-mode resource-constrained project scheduling problems using multi-objective optimization are identified.

scholarly journals Comparison of Heuristic Priority Rules in the Solution of the Resource-Constrained Project Scheduling Problem

2021 ◽  
Vol 13 (17) ◽  
pp. 9956
Author(s):  
Osman Hürol Türkakın ◽  
David Arditi ◽  
Ekrem Manisalı
Keyword(s):  
Resource Allocation ◽  
Project Scheduling ◽  
Resource Constraints ◽  
Priority Rules ◽  
Resource Constrained ◽  
Start Time ◽  
Project Duration ◽  
Resource Constrained Project Scheduling ◽  
Finish Time ◽  
Positional Weight

Resource-constrained project scheduling (RCPS) aims to minimize project duration under limited resource availabilities. The heuristic methods that are often used to solve the RCPS problem make use of different priority rules. The comparative merits of different priority rules have not been discussed in the literature in sufficient detail. This study is a response to this research gap. It compares 17 heuristic priority rules and seeks the best performing heuristic priority rule. This is the first study ever that compares heuristic priority rules by considering combinations of variations in (1) resource allocation procedures, (2) number of activities, (3) number of resource constraints, and (4) resource supply levels. The objective is to understand the relative merits of heuristic rules used in solving the RCPS problem. The findings indicate that the “minimum late finish time” rule generates the shortest predicted project duration when used in parallel resource allocation, whereas the “minimum late start time”, “minimum late finish time”, and the “highest rank of positional weight 2” rules perform best in serial resource allocation. It was also found that parallel resource allocation is slightly superior to serial resource allocation in most instances.

A novel algorithm for solving resource-constrained project scheduling problems: a case study

2019 ◽  
Vol 16 (2) ◽  
pp. 194-215 ◽  
Author(s):  
Mahmood Kasravi ◽  
Amin Mahmoudi ◽  
Mohammad Reza Feylizadeh
Keyword(s):  
Project Scheduling ◽  
Hybrid Algorithm ◽  
Pso Algorithm ◽  
Project Planning ◽  
Heuristic Methods ◽  
Scheduling Problems ◽  
Resource Constrained ◽  
Content Type ◽  
Resource Constrained Project Scheduling

PurposeConstruction projects managers try their best for the project to go according to the plans. They always attempt to complete the projects on time and consistent with the predetermined budgets. Amid so many problems in project planning, the most critical and well-known problem is the Resource-Constrained Project Scheduling Problem (RCPSP). The purpose of this paper is to solve RCPSP using hybrid algorithm ICA/PSO.Design/methodology/approachDue to the existence of various forms for scheduling the problem and also the diversity of constraints and objective functions, myriad of research studies have been conducted in this realm of study. Since most of these problems are NP-hard ones, heuristic and meta-heuristic methods are used for solving these problems. In this research, a novel hybrid method which is composed of meta-heuristic methods of particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) has been used to solve RCPSP. Finally, a railway project has been examined for RCPS Problem in a real-world situation.FindingsAccording to the results of the case study, ICA/PSO algorithm has better results than ICAs and PSO individually.Practical implicationsICA/PSO algorithm could be used for solving problems in a multi-mode situation of activities or considering more constraints on the resources, such as the existence of non-renewable resources and renewable. Based on the case study in construction project, ICA/PSO algorithm has a better solution than PSO and ICA.Originality/valueIn this study, by combining PSO and ICA algorithms and creating a new hybrid algorithm, better solutions have been achieved in RCPSP. In order to validate the method, standard problems available in PSPLib library were used.

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