TLBO with variable weights applied to shop scheduling problems
作者机构：Electronics DivisionInstitute of Aeronautics and SpacePraca Marechal Eduardo Gomes50Sao Josedos Campos 12228-904Brazil Computer Science DepartmentFederal University of CearaRua Campus do PiciSnFortaleza 60440-554Brazil
出 版 物：《CAAI Transactions on Intelligence Technology》 (智能技术学报（英文）)
年 卷 期：2019年第4卷第3期
页 面：148-158页
核心收录：
学科分类：0810[工学-信息与通信工程] 1205[管理学-图书情报与档案管理] 0839[工学-网络空间安全] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：Conselho Nacional de Desenvolvimento Científico e Tecnológico CNPq (305048/2016-3)
主 题：TLBO variable weights shop scheduling problems
摘 要：The teaching–learning-based optimisation (TLBO) algorithm is a population-based metaheuristic inspired on the teaching–learning process observed in a classroom. It has been successfully used in a wide range of applications. In this study, the authors present a variant version of TLBO. In the proposed version, different weights are assigned to students during the student phase, with higher weights being assigned to students with better solutions. Three different approaches to assign weights are investigated. Numerical experiments with benchmark instances of the flow-shop and the job-shop scheduling problems are carried out to investigate the performance of the proposed approaches. They compare the proposed approaches with the original TLBO algorithm and with two variants of TLBOs proposed in the literature in terms of solution quality, convergence speed and simulation time. The results obtained by the application of a Friedman statistical test showed that the proposed approaches outperformed the original version of TLBO in terms of convergence, with no significant losses in the average makespan. The additional simulation time required by the proposed approaches is small. The best performance was achieved with the approach of assigning a fixed weight to half the students with the best solutions and assigning zero to other students.
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