Impacts of different objective functions on resource leveling in Line-of-Balance scheduling

2015 ◽  
Vol 20 (1) ◽  
pp. 58-67 ◽  
Author(s):  
Atilla Damci ◽  
David Arditi ◽  
Gul Polat
Keyword(s):  
Objective Functions ◽  
Resource Leveling ◽  
Line Of Balance

Resource Leveling Based on Line of Balance and Constraint Programming

2018 ◽  
Vol 33 (10) ◽  
pp. 864-884 ◽  
Author(s):  
Yuanjie Tang ◽  
Quanxin Sun ◽  
Rengkui Liu ◽  
Futian Wang
Keyword(s):  
Constraint Programming ◽  
Resource Leveling ◽  
On Line ◽  
Line Of Balance

scholarly journals Optimization of resource leveling problem under multiple objective criteria using a symbiotic organisms search

2019 ◽  
Vol 21 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Doddy Prayogo ◽  
Christianto Tirta Kusuma
Keyword(s):  
Particle Swarm Optimization ◽  
Resource Management ◽  
Objective Function ◽  
Multiple Objective ◽  
Objective Functions ◽  
Swarm Optimization ◽  
Cost Overruns ◽  
Symbiotic Organisms Search ◽  
Resource Leveling ◽  
Symbiotic Organisms

Bad scheduling and resource management can cause delays or cost overruns. Optimization in solving resource leveling is necessary to avoid those problems. Several objective criteria are used to solve resource leveling. Each of them has the same objective, which is to reduce the fluctuation of resource demand of the project. This study compares the performance of particle swarm optimization (PSO) and symbiotic organisms search (SOS) in solving resource leveling problems using separate objective functions in order to find which one produces a better solution. The results show that SOS produced a better solution than PSO, and one objective function is better in solving resource leveling than the others.

scholarly journals IMPACTS OF DIFFERENT OBJECTIVE FUNCTIONS ON RESOURCE LEVELING IN CONSTRUCTION PROJECTS: A CASE STUDY

2014 ◽  
Vol 20 (4) ◽  
pp. 537-547 ◽  
Author(s):  
Atilla Damci ◽  
Gul Polat
Keyword(s):  
Objective Function ◽  
Resource Utilization ◽  
Construction Projects ◽  
Critical Path ◽  
Industrial Building ◽  
Objective Functions ◽  
Critical Path Method ◽  
Resource Leveling ◽  
Average Improvement ◽  
The One

A review of the recent literature on the models that focus on resource leveling in Critical Path Method networks shows that different objective functions have been used to optimize resource utilization. The main objective of this study is to investigate the impacts of using different objective functions on resource utilization histograms in Critical Path Method networks. For this purpose, nine different resource leveling objective functions were optimized via a genetic algorithm-based model. The model was developed using actual data obtained from a steel framed industrial building construction project. It was found that each of these objective functions generates different resource utilization histograms. In order to determine the improvement levels achieved by resource leveling using nine different objective functions, the improvement percentage in each parameter and the average improvement percentage for each objective function were calculated. Even though the objective function that involves the minimization of the sum of the square of the deviations in daily resource usage provided the best average improvement percentage in the studied case, another objective function(s) may provide better average improvement percentage in different projects. The contractor should consider all objective functions for resource leveling and select the one(s) that provides the best average improvement percentage.

Resource Leveling in Line-of-Balance Scheduling

2013 ◽  
Vol 28 (9) ◽  
pp. 679-692 ◽  
Author(s):  
Atilla Damci ◽  
David Arditi ◽  
Gul Polat
Keyword(s):  
Resource Leveling ◽  
Line Of Balance

scholarly journals Resource Leveling Based on Backward Controlling Activity in Line of Balance

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Lihui Zhang ◽  
Yaping Tang ◽  
Jianxun Qi
Keyword(s):  
Resource Management ◽  
Balance Method ◽  
Design Algorithm ◽  
Project Duration ◽  
Resource Leveling ◽  
Use Of Resources ◽  
Matlab Program ◽  
Proposed Model ◽  
Pipeline Project ◽  
Line Of Balance

The line of balance method that provides continuous and uninterrupted use of resources is one of the best methods for repetitive project resource management. This paper develops a resource leveling algorithm based on the backward controlling activity in line of balance. The backward controlling activity is a kind of special activity, and if its duration is prolonged the project duration could be reduced. It brings two advantages to the resource leveling: both the resource allocated on the backward activity and the project duration are reduced. A resource leveling algorithm is presented which permits the number of crews of the backward controlling activity to be reduced until the terminal situation is reached, where the backward controlling activity does not exist or the number of crews cannot be reduced. That adjustment enables the productivity of all activities to be consistent. An illustrative pipeline project demonstrates the improvement in resource leveling. And this study designed a MATLAB program to execute the design algorithm. The proposed model could help practitioners to achieve the goals of both resource leveling and project duration reduction without increasing any resource.

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

The Project Scheduling and Decision Mechanism Based on the Multi-Resource Leveling

2011 ◽  
Author(s):  
Hsiang-Hsi Huang ◽  
◽  
Jia-Chen Shiu ◽  
Tai-Lin Chen ◽  
◽  
...  
Keyword(s):  
Project Scheduling ◽  
Resource Leveling ◽  
Decision Mechanism

Multi-Objective Design Problem of Tire Wear and Visualization of Its Pareto Solutions2

2006 ◽  
Vol 34 (3) ◽  
pp. 170-194 ◽  
Author(s):  
M. Koishi ◽  
Z. Shida
Keyword(s):  
Inverse Problems ◽  
Conceptual Design ◽  
Dimensional Space ◽  
Design Stage ◽  
Objective Functions ◽  
Pareto Solutions ◽  
Design Problems ◽  
Multi Objective ◽  
Design Engineers ◽  
Design Variables

Abstract Since tires carry out many functions and many of them have tradeoffs, it is important to find the combination of design variables that satisfy well-balanced performance in conceptual design stage. To find a good design of tires is to solve the multi-objective design problems, i.e., inverse problems. However, due to the lack of suitable solution techniques, such problems are converted into a single-objective optimization problem before being solved. Therefore, it is difficult to find the Pareto solutions of multi-objective design problems of tires. Recently, multi-objective evolutionary algorithms have become popular in many fields to find the Pareto solutions. In this paper, we propose a design procedure to solve multi-objective design problems as the comprehensive solver of inverse problems. At first, a multi-objective genetic algorithm (MOGA) is employed to find the Pareto solutions of tire performance, which are in multi-dimensional space of objective functions. Response surface method is also used to evaluate objective functions in the optimization process and can reduce CPU time dramatically. In addition, a self-organizing map (SOM) proposed by Kohonen is used to map Pareto solutions from high-dimensional objective space onto two-dimensional space. Using SOM, design engineers see easily the Pareto solutions of tire performance and can find suitable design plans. The SOM can be considered as an inverse function that defines the relation between Pareto solutions and design variables. To demonstrate the procedure, tire tread design is conducted. The objective of design is to improve uneven wear and wear life for both the front tire and the rear tire of a passenger car. Wear performance is evaluated by finite element analysis (FEA). Response surface is obtained by the design of experiments and FEA. Using both MOGA and SOM, we obtain a map of Pareto solutions. We can find suitable design plans that satisfy well-balanced performance on the map called “multi-performance map.” It helps tire design engineers to make their decision in conceptual design stage.

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