Genetic Algorithm-Based Multi-Objective Model for Scheduling of Linear Construction Projects Under Extreme Weather Conditions

2012 ◽  
Author(s):  
Ahmed B. Senouci ◽  
Saleh A. Mubarak
Keyword(s):  
Genetic Algorithm ◽  
Construction Projects ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Multi Objective ◽  
Objective Model

scholarly journals MULTIOBJECTIVE OPTIMIZATION MODEL FOR SCHEDULING OF CONSTRUCTION PROJECTS UNDER EXTREME WEATHER

2016 ◽  
Vol 22 (3) ◽  
pp. 373-381 ◽  
Author(s):  
Ahmed B. SENOUCI ◽  
Saleh A. MUBARAK
Keyword(s):  
Optimization Model ◽  
Construction Projects ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Construction Time ◽  
Multi Objective ◽  
Trade Offs ◽  
The Impact ◽  
Construction Schedules ◽  
Cost Of Construction

Extreme weather significantly impacts construction schedules and costs and can be a source of schedule de­lays and budget overruns. A multi-objective optimization model, presented herein for the scheduling of construction projects under extreme weather conditions, can generate optimal/near optimal schedules that minimize the time and cost of construction projects in extreme weather regions. The model computations are organized as follows: (1) a scheduling module for developing practical schedules for construction projects, (2) a cost module for computing total project cost, and (3) a multi-objective module for determining optimal/near optimal trade-offs between project time and cost. Two practical examples of the effects of extreme weather on construction time and direct cost are provided, the first of which shows the impact of extreme weather on construction time and cost, and the second of which demonstrates the ability of the model to generate and visually present the optimal trade-offs between the duration and costs of construction projects under extreme weather conditions.

Multi-objective resilience enhancement program in smart grids during extreme weather conditions

2021 ◽  
Vol 129 ◽  
pp. 106824
Author(s):  
Rahman Ashrafi ◽  
Meysam Amirahmadi ◽  
Mohammad Tolou-Askari ◽  
Vahid Ghods
Keyword(s):  
Smart Grids ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Multi Objective

scholarly journals Fuzzy Multi-Objective Genetic Algorithm Based Resource Constrained Time-Cost Trade-Off Model under Uncertain Environment

2021 ◽  
Vol 9 (8) ◽  
pp. 1126-1133
Author(s):  
Ashish Sharma
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Construction Projects ◽  
Risk Level ◽  
Pareto Optimal ◽  
Time Cost ◽  
Trade Off ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm

Abstract: In every construction project, the time and cost are the two most important objectives/factors to be considered. Clients and contractors should strive to optimize the project time and cost to maximize the return. Resources are also one of the major constraints of the construction projects. In recent years, several studies have been conducted to optimize the time and cost of project under constraint conditions of resources. Since most studies assume the time and cost as deterministic parameters, uncertainties should be considered in estimating the time and cost of the project's activities when minimizing the duration and cost of the project. For this purpose, this paper embeds the fuzzy logic to handle the uncertainties in estimating the time and cost. Besides, the multi-objective genetic algorithm (MOGA) is used to develop the resourceconstrained time-cost trade-off model. Alpha-cut approach is utilized to define the accepted risk level of decision maker. The efficiency of the proposed model is demonstrated through solvinga case study project of highway construction. The results of case study project provide a set of Pareto-optimal solutions. The developed model encourage the decision making process by choosing specified risk levels and utilizing the related Pareto-front. Keywords: Construction projects, time-cost trade-off, uncertainties, fuzzy logic, MOGA,Pareto-optimal solution.

A Multi-Objective Model about Period Train Timetable Problem and a Genetic Algorithm Based on Job-Shop Problem

2011 ◽  
Vol 48-49 ◽  
pp. 56-59
Author(s):  
Xiao Qiu Jia ◽  
Xiao Yu Guan
Keyword(s):  
Genetic Algorithm ◽  
Job Shop ◽  
Single Model ◽  
Multi Objective ◽  
Train Timetable ◽  
Objective Model ◽  
Basic Ideas ◽  
Timetable Problem

At present, periodic train timetable problem (PTTP) becomes one of the hot topics home and abroad. On the basic of present theories and methods about periodic and non-periodic train timetable problem, the thesis constructs a multi-objectives model for the PTTP, transfers it into a single model with multi-priorities structure, and designs a genetic algorithm in a given period by the basic ideas on solving job shop problem. Finally, the paper gives out a instance for Jingjin railroad to show effectiveness of the algorithm.

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