{"title":"基于新初始种群方法的时间-成本权衡优化","authors":"V. Toğan, M. A. Eirgash","doi":"10.18400/TEKDERG.410934","DOIUrl":null,"url":null,"abstract":"Considering the competitive environment in all industries, completion on time is crucial for the stakeholders of a project. This favorable target is achieved by finding the optimal set of time-cost alternatives and this is known as time-cost trade-off problem (TCTP) in the literature. In this study, a new initial population approach is presented to improve the quality of the optimal set of time-cost alternatives. It put a predefined number of the solutions of the single objective TCTP into the initial population of teaching learning-based algorithm, which is utilized as an optimizer for the multi-objective optimization of TCTP. Hence, it is aimed to descend the randomness on initial population and to decrease the searching effort to catch the optimal set of time-cost alternatives in the search space. The proposed methodology is tested on a series of benchmark problems and the obtained results are compared with those available in the technical literature. It can produce good solutions as effective as with other techniques applied for simultaneous optimization of TCTPs.","PeriodicalId":49442,"journal":{"name":"Teknik Dergi","volume":" ","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Time-Cost Trade-Off Optimization with a New Initial Population Approach\",\"authors\":\"V. Toğan, M. A. Eirgash\",\"doi\":\"10.18400/TEKDERG.410934\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Considering the competitive environment in all industries, completion on time is crucial for the stakeholders of a project. This favorable target is achieved by finding the optimal set of time-cost alternatives and this is known as time-cost trade-off problem (TCTP) in the literature. In this study, a new initial population approach is presented to improve the quality of the optimal set of time-cost alternatives. It put a predefined number of the solutions of the single objective TCTP into the initial population of teaching learning-based algorithm, which is utilized as an optimizer for the multi-objective optimization of TCTP. Hence, it is aimed to descend the randomness on initial population and to decrease the searching effort to catch the optimal set of time-cost alternatives in the search space. The proposed methodology is tested on a series of benchmark problems and the obtained results are compared with those available in the technical literature. It can produce good solutions as effective as with other techniques applied for simultaneous optimization of TCTPs.\",\"PeriodicalId\":49442,\"journal\":{\"name\":\"Teknik Dergi\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Teknik Dergi\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.18400/TEKDERG.410934\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Teknik Dergi","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.18400/TEKDERG.410934","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
Time-Cost Trade-Off Optimization with a New Initial Population Approach
Considering the competitive environment in all industries, completion on time is crucial for the stakeholders of a project. This favorable target is achieved by finding the optimal set of time-cost alternatives and this is known as time-cost trade-off problem (TCTP) in the literature. In this study, a new initial population approach is presented to improve the quality of the optimal set of time-cost alternatives. It put a predefined number of the solutions of the single objective TCTP into the initial population of teaching learning-based algorithm, which is utilized as an optimizer for the multi-objective optimization of TCTP. Hence, it is aimed to descend the randomness on initial population and to decrease the searching effort to catch the optimal set of time-cost alternatives in the search space. The proposed methodology is tested on a series of benchmark problems and the obtained results are compared with those available in the technical literature. It can produce good solutions as effective as with other techniques applied for simultaneous optimization of TCTPs.
期刊介绍:
The scope of Teknik Dergi is naturally confined with the subjects falling in the area of civil engineering. However, the area of civil engineering has recently been significantly enlarged, even the definition of civil engineering has somewhat changed.
Half a century ago, engineering was simply defined as “the art of using and converting the natural resources for the benefit of the mankind”. Today, the same objective is expected to be realised (i) by complying with the desire and expectations of the people concerned and (ii) without wasting the resources and within the sustainability principles. This change has required an interaction between engineering and social and administrative sciences. Some subjects at the borderline between civil engineering and social and administrative sciences have consequently been included in the area of civil engineering.
Teknik Dergi defines its scope in line with this understanding. However, it requires the papers falling in the borderline to have a significant component of civil engineering.