Fuzzy Based Project Time-Cost Optimization Using Simulated Annealing Search Technique

2014 ◽  
Vol 5 (1) ◽  
pp. 90-103 ◽  
Author(s):  
Khan Md. Ariful Haque ◽  
M. Ahsan Akhtar Hasin
Keyword(s):  
Simulated Annealing ◽  
Cost Optimization ◽  
Process Time ◽  
Time Cost ◽  
Deterministic Models ◽  
Productivity Level ◽  
Proposed Model ◽  
Cut Method ◽  
Project Scheduling Problem ◽  
Fuzzy Logic Theory

The Project time-cost optimization is inherently a complex task. Because of various kinds of uncertainties, such as weather, productivity level, inflation, human factors etc. during project execution process, time and cost of each activity may vary significantly. The complexity multiplies several folds when the operational times are not deterministic, rather fuzzy in nature. Therefore, deterministic models for time-cost optimization are not yet efficient. It is very difficult to find the exact solution of savings in both time and cost. To make such problems realistic, triangular fuzzy numbers and the concept of a-cut method in fuzzy logic theory are employed to model the problem. Because of NP-hard nature of the project scheduling problem, this paper develops a simple approach with Simulated Annealing (SA) based searching technique. The proposed model leads the decision makers to choose the desired solution under different values of a-cut. Finally, taking a real project, the performance of SA has been tested.

scholarly journals Fuzzy Based Project Time-Cost Optimization Using Simulated Annealing Search Technique

2016 ◽  
pp. 1473-1486
Author(s):  
Khan Md. Ariful Haque ◽  
M. Ahsan Akhtar Hasin
Keyword(s):  
Simulated Annealing ◽  
Cost Optimization ◽  
Process Time ◽  
Time Cost ◽  
Deterministic Models ◽  
Productivity Level ◽  
Proposed Model ◽  
Cut Method ◽  
Project Scheduling Problem ◽  
Fuzzy Logic Theory

The Project time-cost optimization is inherently a complex task. Because of various kinds of uncertainties, such as weather, productivity level, inflation, human factors etc. during project execution process, time and cost of each activity may vary significantly. The complexity multiplies several folds when the operational times are not deterministic, rather fuzzy in nature. Therefore, deterministic models for time-cost optimization are not yet efficient. It is very difficult to find the exact solution of savings in both time and cost. To make such problems realistic, triangular fuzzy numbers and the concept of a-cut method in fuzzy logic theory are employed to model the problem. Because of NP-hard nature of the project scheduling problem, this paper develops a simple approach with Simulated Annealing (SA) based searching technique. The proposed model leads the decision makers to choose the desired solution under different values of a-cut. Finally, taking a real project, the performance of SA has been tested.

scholarly journals STUDY AND APPLY ACO ALGORITHM IN TIME-COST OPTIMIZATION OF CONSTRUCTION PROJECT

2010 ◽  
Vol 13 (1) ◽  
pp. 17-30
Author(s):  
Luan Hong Pham ◽  
Nhan Thanh Duong
Keyword(s):  
Cost Optimization ◽  
Construction Project ◽  
Heuristic Method ◽  
Ant Colony ◽  
Ant Colony System ◽  
Time Cost ◽  
Project Duration ◽  
Proposed Model ◽  
Feasible Solutions ◽  
Computational Resources

Time-cost optimization problem is one of the most important aspects of construction project management. In order to maximize the return, construction planners would strive to optimize the project duration and cost concurrently. Over the years, many researches have been conducted to model the time-cost relationships; the modeling techniques range from the heuristic method and mathematical approach to genetic algorithm. In this paper, an evolutionary-based optimization algorithm known as ant colony optimization (ACO) is applied to solve the multi-objective time-cost problem. By incorporating with the modified adaptive weight approach (MAWA), the proposed model will find out the most feasible solutions. The concept of the ACO-TCO model is developed by a computer program in the Visual Basic platforms. An example was analyzed to illustrate the capabilities of the proposed model and to compare against GA-based TCO model. The results indicate that ant colony system approach is able to generate better solutions without making the most of computational resources which can provide a useful means to support construction planners and managers in efficiently making better time-cost decisions.

scholarly journals Extremal-Micro Genetic Algorithm Model for Time-Cost Optimization with Optimal Labour Productivity

2021 ◽  
Vol 67 (12) ◽  
pp. 682-691
Author(s):  
Sivakumar A ◽  
Bagath Singh N ◽  
Sathiamurthi P ◽  
Karthi Vinith K.S.
Keyword(s):  
Genetic Algorithm ◽  
Labour Productivity ◽  
Cost Optimization ◽  
Model Performance ◽  
Time Cost ◽  
Production Time ◽  
Proposed Model ◽  
Bus Body ◽  
Micro Genetic Algorithm ◽  
Genetic Algorithm Model

In a highly competitive manufacturing environment, it is critical to balance production time and cost simultaneously. Numerous attempts have been made to provide various solutions to strike a balance between these factors. However, more effort is still required to address these challenges in terms of labour productivity. This study proposes an integrated substitution and management improvement technique for enhancing the effectiveness of labour resources and equipment. Furthermore, in the context of time-cost optimization with optimal labour productivity, an extremal-micro genetic algorithm (Ex-μGA) model has been proposed. A real-world case from the labour-intensive medium-scale bus body fabricating industry is used to validate the proposed model performance. According to the results, the proposed model can optimize production time and cost by 34 % and 19 %, respectively, while maintaining optimal labour productivity. In addition, this study provides an alternative method for dealing with production parameter imbalances and assisting production managers in developing labour schedules more effectively.

scholarly journals AN ANT COLONY SYSTEM BASED DECISION SUPPORT SYSTEM FOR CONSTRUCTION TIME-COST OPTIMIZATION

2012 ◽  
Vol 18 (4) ◽  
pp. 580-589 ◽  
Author(s):  
Yanshuai Zhang ◽  
S. Thomas Ng
Keyword(s):  
Optimization Problems ◽  
Cost Optimization ◽  
Ant Colony ◽  
Ant Colony System ◽  
Time Cost ◽  
Construction Time ◽  
Project Duration ◽  
Test Study ◽  
Proposed Model ◽  
Computational Resources

Time and cost are the two most important factors to be considered in every construction project. In order to maximize the profit, both the client and contractor would strive to minimize the project duration and cost concurrently. In the past, most of the research studies related to construction time and cost assumed time to be constant, leaving the analyses based purely on a single objective of cost. Acknowledging this limitation, an evolutionary-based optimization algorithm known as an ant colony system is applied in this study to solve the multi-objective time-cost optimization problems. In this paper, a model is developed using Visual Basic for Application™ which is integrated with Microsoft Project™. Through a test study, the performance of the proposed model is compared against other analytical methods previously used for time-cost modeling. The results show that the model based on the ant colony system techniques can generate better solutions without utilizing excessive computational resources. The model, therefore, provides an efficient means to support planners and managers in making better time-cost decisions efficiently.

Time–Cost Optimization Model Considering Float-Consumption Impact

2015 ◽  
Vol 141 (5) ◽  
pp. 04015001 ◽  
Author(s):  
Rana A. Al Haj ◽  
Sameh M. El-Sayegh
Keyword(s):  
Optimization Model ◽  
Cost Optimization ◽  
Time Cost

scholarly journals Adaptive model to support business process reengineering

2021 ◽  
Vol 7 ◽  
pp. e505
Author(s):  
Noha Ahmed Bayomy ◽  
Ayman E. Khedr ◽  
Laila A. Abd-Elmegid
Keyword(s):  
Business Process ◽  
Success Factors ◽  
Business Processes ◽  
Business Environment ◽  
Process Time ◽  
Critical Success ◽  
Proposed Model ◽  
Before And After ◽  
Time Cycle ◽  
The One

The one constant in the world is change. The changing dynamics of business environment enforces the organizations to re-design or reengineer their business processes. The main objective of such reengineering processes is to provide services or produce products with the possible lowest cost, shortest time, and best quality. Accordingly, Business Process Re-engineering (BPR) provides a roadmap of how to efficiently achieve the operational goals in terms of enhanced flexibility and productivity, reduced cost, and improved quality of service or product. In this article, we propose an efficient model for BPR. The model specifies where the breakdowns occur in BPR implementation, justifies why such breakdowns occur, and proposes techniques to prevent their occurrence again. The proposed model has been built based on two main sections. The first section focuses on integrating Critical Success Factors (CSFs) and the performance of business processes during the reengineering processes. Additionally, it implements the association rule mining technique to investigate the relationship between CSFs and different business processes. The second section aims to measure the performance of business processes (intended success of BPR) by process time, cycle time, quality and cost before and after reengineering processes. A case study of the Egyptian Tax Authority (ETA) is used to test the efficiency of the proposed model.

scholarly journals A Cost Optimization Model for Multiresource Leveling Problem without Project Duration Constraint

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Qingyou Yan ◽  
Qian Zhang ◽  
Xin Zou
Keyword(s):  
Optimization Model ◽  
Cost Optimization ◽  
Resource Usage ◽  
Project Duration ◽  
Resource Demand ◽  
Resource Leveling ◽  
Proposed Model ◽  
Liquidated Damages ◽  
The Relationship

The study of traditional resource leveling problem aims at minimizing the resource usage fluctuations and obtaining sustainable resource supplement, which is accomplished by adjusting noncritical activities within their start and finish time. However, there exist limitations in terms of the traditional resource leveling problem based on the fixed project duration. This paper assumes that the duration can be changed in a certain range and then analyzes the relationship between the scarce resource usage fluctuations and project cost. This paper proposes an optimization model for the multiresource leveling problem. We take into consideration five kinds of cost: the extra hire cost when the resource demand is greater than the resource available amount, the idle cost of resource when the resource available amount is greater than the resource demand, the indirect cost related to the duration, the liquidated damages when the project duration is extended, and the incentive fee when the project duration is reduced. The optimal objective of this model is to minimize the sum of the aforementioned five kinds of cost. Finally, a case study is examined to highlight the characteristic of the proposed model at the end of this paper.

Sign in / Sign up

Export Citation Format

Share Document