{"title":"A heuristic algorithm for the stochastic vehicle routing problems with soft time windows","authors":"Zigang G. Guo, K. Mak","doi":"10.1109/CEC.2004.1331067","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331067","url":null,"abstract":"A very complicated class of vehicle routing problem (VRP), stochastic vehicle routing problem with soft time windows (SVRPSTW), is studied. In this kind of problem the customer demand and the presence of the customer are assumed to be uncertain. And each customer is bounded by a service time window but lateness arrival at the customer is allowed by a penalty added into the total cost. The service vehicle returns to the depot whenever its capacity is attained or exceeded, and resumes its collections along the planned route. After describing the concept of SVRPSTW, a mathematical programming formulation is developed in order to study the effects of the stochastic demands and customers on transportation. A genetic based algorithm is proposed for this intractable problem in order to obtain optimal or near optimal solutions that have minimum total cost. Computational examples on a group of instances are given, showing the proposed approach is a simple but effective ways to solve such problems.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115441304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the performance of evolutionary algorithms with life-time adaptation in dynamic fitness landscapes","authors":"R. Eriksson, Björn Olsson","doi":"10.1109/CEC.2004.1331046","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331046","url":null,"abstract":"This work demonstrates how the efficiency of evolutionary algorithms in dynamic environments can be improved by use of life-time adaptation. Our results contradict the hypothesis that there would be a tradeoff between designing and tuning EAs for static and dynamic environments, in which improved efficiency in one type of environment would decrease the efficiency in the other. In contrast, we show that the inclusion of life-time adaptation can result in EAs that outperform traditional EAs in both static and dynamic environments. Since the performance of EAs with life-time adaptation in dynamic environments are currently poorly understood at best, we conduct an extensive evaluation of the performance of these EAs on combinatorial and continuous dynamic global optimization problems with well-defined characteristics. In doing so, we propose improved benchmark dynamic fitness functions for both the combinatorial and continuous domains, which we have termed random dynamics NK-landscapes and structured moving peaks landscapes, respectively.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122995874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A GA-based integrated approach to model-assisted matching and pose estimation for automated visual inspection applications","authors":"S. Hati, S. Sengupta","doi":"10.1109/CEC.2004.1331053","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331053","url":null,"abstract":"We present a genetic algorithm based integrated approach to model-assisted matching and pose estimation for automated visual inspection applications. Unlike the past works reported in literature, this approach does not consider the matching between the model and the image of the object to be essential step prior to pose estimation. A set of matched vertices sequence and poses are hypothesized using a newly proposed composite chromosome structure and these are genetically evolved until a reasonably accurate pose is determined. Our algorithm demonstrates its robustness against noise as well as missing and spurious object vertices.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114955599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Functional localization of genetic network programming and its application to a pursuit problem","authors":"S. Eto, K. Hirasawa, Jinglu Hu","doi":"10.1109/CEC.2004.1330925","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330925","url":null,"abstract":"According to the knowledge of brain science, it is suggested that there exists cerebral functional localization, which means that a specific part of the cerebrum is activated depending on various kinds of information human receives. The aim of this paper is to build an artificial model to realize functional localization based on genetic network programming (GNP), a new evolutionary computation method recently developed. GNP has a directed graph structure suitable for realizing functional localization. We studied the basic characteristics of the proposed system by making GNP work in a functionally localized way.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123877586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Constrained optimization problem solving using estimation of distribution algorithms","authors":"P. A. Simionescu, D. Beale, G. Dozier","doi":"10.1109/CEC.2004.1330870","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330870","url":null,"abstract":"Two variants of estimation of distribution algorithm (EDA) are tested solving several continuous optimization problems with constraints. Numerical experiments are conducted and comparison is made between constraint handling using several types of penalty and repair operators in case of both elitist and nonelitist implementation of the EDA's. Graphical display and animations of representative runs of the best and worst performers proved useful in enhancing the understanding of how such algorithms work.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125833888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Hernández, Fernando Niño, Julián García, D. Dasgupta
{"title":"On geometric and statistical properties of the attractors of a generic evolutionary algorithm","authors":"G. Hernández, Fernando Niño, Julián García, D. Dasgupta","doi":"10.1109/CEC.2004.1331039","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331039","url":null,"abstract":"In this work, evolutionary algorithms are modeled as random dynamical systems. The combined action of selection and variation is expressed as a stochastic operator acting on the space of populations. The long term behavior of selection and variation is studied separately. Then the combined effect is analyzed by characterizing the attractor and stationary measure of the dynamics. As a main result it is proved that the stationary measure is supported on populations made up of optimizers. Also, some experiments are carried out in order to visualize the evolvable populations, the attractor sets and the stationary measure. Some geometric properties of such sets are discussed.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129589035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using SAT scores as predictors for future academic success","authors":"D. Cohen","doi":"10.1109/CEC.2004.1330923","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330923","url":null,"abstract":"In the past decade, there has been a lot of scrutiny placed on the value of SAT scores. Various collegiate institutions, such as the entire California State school system have dropped the requirement for students to submit SAT scores to the admissions board for entry. Reasons for this vary from institution to institution and range from the selfish to the altruistic. On one side of the spectrum, the thought is that by making the SAT scores optional, average SAT scores at the institution rise, as the applicants well self select who submits scores. On the other end of the spectrum, some institutions believe that the SAT test is unfair, as certain socioeconomic groups tend to fair better on the test than others. Regardless of the reason, institutions are throwing away a piece of data that could possibly give some insight into an applicant's likelihood of success. This paper looks at the question of whether or not SAT scores are a reasonably good of indicator of future collegiate academic success. This theory was tested through the use of a logical rule set created using genetic algorithms. Results seem to indicate that SAT scores are in fact, good predictors of future collegiate success.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"143 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129484452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The force model: concept, behavior, interpretation","authors":"R. Salomon","doi":"10.1109/CEC.2004.1330987","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330987","url":null,"abstract":"Most experiments in research on autonomous agents and mobile robots are performed either in simulation or on robots with static physical properties; evolvable hardware is hardly ever used. One of the very rare exceptions is the eyebot on which Lichtensteiger and Eggenberger (1999) have evolved simplified insect eyes. Even though substantially improved, the evolutionary models currently applied still lack both scalability and noise resistance. To tackle these problems, this paper proposes a biologically-inspired force model for this class of real-world applications. The simulation results clearly indicate that this model provides a significant improvement over existing limitations. Furthermore, this paper argues that the force model is of more general utility.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124645121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Robust, reversible, nano-scale, femto-second-switching circuits and their evolution","authors":"H. D. Garis, T. Batty","doi":"10.1109/CEC.2004.1330918","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330918","url":null,"abstract":"This paper introduces conceptual problems that arise in the next 10-20 years as electronic circuits reach nanometer scale, i.e. the size of molecules. Such circuits are impossible to make perfectly, due to the inevitable fabrication faults in chips with an Avogrado number of components. Hence, they need to be constructed so that they are robust to faults. They also need to be (as far as possible) reversible circuits, to avoid the heat dissipation problem if bits of information are routinely wiped out during the computational process. They also have to be local if the switching times reach femto-seconds, which is possible now with quantum optics. This paper discusses some of the conceptual issues involved in trying to build circuits that satisfy all these criteria, i.e. that they are robust, reversible and local. We propose an evolutionary engineering based model that meets all these criteria, and provide some experimental results to justify it.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"349 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131145673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Issues in evolving GP based classifiers for a pattern recognition task","authors":"A. Teredesai, V. Govindaraju","doi":"10.1109/CEC.2004.1330899","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330899","url":null,"abstract":"This paper discusses issues when evolving genetic programming (GP) classifiers for a pattern recognition task such as handwritten digit recognition. Developing elegant solutions for handwritten digit classification is a challenging task. Similarly, design and training of classifiers using genetic programming is a relatively new approach in pattern recognition as compared to other traditional techniques. Several strategies for GP training are outlined and the empirical observations are reported. The issues we faced such as training time, a variety of fitness landscapes and accuracy of results are discussed. Care has been taken to test GP using a variety of parameters and on several handwritten digits datasets.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129932972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}