Proceedings of the International Conference on Industrial Engineering and Operations Management , 2019
This research focuses on the performance comparison of real-coded Genetic Algorithms (GA) and Bio... more This research focuses on the performance comparison of real-coded Genetic Algorithms (GA) and Biogeography-based Optimization (BBO) algorithms. Specifically, it takes three modified versions of the original algorithms made suitable for continuous operations (real-coded) – the standard real-coded GA (SRCGA), the real-coded GA with mathematical projection (RCGA-P) and the real coded-biogeographybased optimization algorithm (RCBBO); then conducts a performance-based comparison of these three with respect to convergence, speed and robustness criteria. This comparison was done using 52 standard optimization benchmark problems over four, ten and twenty dimensions. Results show that overall, SRCGA outperforms the others for speed while RCGA-P was the most robust of the three. The major value-add in performance of RCBBO was mainly from speed as in two dimensions, it delivers better speed than the two real-coded GA
Many Nigerians suffer from end stage kidney disease and require some form of renal replacement th... more Many Nigerians suffer from end stage kidney disease and require some form of renal replacement therapy (either dialysis or kidney transplantation) to sustain life. More than 50 parameters may be monitored while providing a kidney dialysis treatment. This work explored and analyzed the massive data generated for several years from the kidney patients in the University College Hospital (UCH), Ibadan using data mining technique. This is done by using Artificial Neural Network technique to select the input variables,
weight, and connectivity structure to determine optimal network topology and to train the system for learning. This helps to determine the features that are predictive of a patient life expectancy, detect the existence of renal failure in a patient, and to predict kidney dialysis survival. This work thus provides Physicians with an instrument that can automatically assess the dialysis service performance and support better understanding of the evaluation results.
"Genetic algorithms are efficient global optimizers, but they are weak in performing fine grained... more "Genetic algorithms are efficient global optimizers, but they are weak in performing fine grained local searches. In this paper, the local search capability of genetic algorithm is improved by hybridizing real coded genetic algorithm with ‘uniform random’ local search to form a hybrid real coded genetic algorithm termed ‘RCGAu’. The incorporated local technique is applied to all newly created offspring so that each offspring solution is given the opportunity to effectively search its local neighborhood for the best local optimum. Numerical experiments show that the performance of RCGA is remarkably improved by the uniform random local search technique."
Proceeding GECCO '13 Companion Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion
In this paper, a real-coded genetic algorithm (RCGA) which incorporates an exploratory search mec... more In this paper, a real-coded genetic algorithm (RCGA) which incorporates an exploratory search mechanism based on vector projection termed projection-based RCGA (PRCGA) is benchmarked on the noisefree BBOB 2013 testbed. It is an enhanced version of RCGA-P in [22, 23]. The projection operator incorporated in PRCGA shows promising exploratory search capability in some problem landscape. PRCGA is equipped with a multiple independent restart mechanism and a stagnation alleviation mechanism. The maximum number of function evaluations (#FEs) for each test run is set to 105 times the problem dimension. PRCGA shows encouraging results on several problems in the low and moderate search dimensions. It is able to solve each type of problem with the dimension up to 40 with lower precision but not all the functions to the desired level of accuracy of 10-8 especially for high conditioning and multi-modal functions within the specified maximum #FEs.
In this paper, a set of new real-coded genetic algorithms (RCGAs) with local and global explorato... more In this paper, a set of new real-coded genetic algorithms (RCGAs) with local and global exploratory search capabilities are proposed. The search capabilities are based on the inclusion of a modified crossover (MC) procedure and a new global exploratory method in RCGA. The global exploratory method is based on vector projection while the MC procedure is based on a limited version of the pattern search method. These modifications are introduced to increase the efficiency and robustness of RCGAs through better local and global exploration of the search region. An experimental study of the new algorithms was carried out using a set of 57 test problems. Statistical analyses and comparisons of the newalgorithms with standard real-coded genetic algorithm (SRCGA) and some recent global optimization algorithms were carried out. Results obtained show that the modifications remarkably improve the performance of RCGAs across the test problems.
Purpose The purpose of this paper is to consider the problem of university lecture timetabling.... more Purpose The purpose of this paper is to consider the problem of university lecture timetabling. Timetabling deals with the problem of placing certain resources into a limited number of time slots, subject to given constraints, in order to satisfy a set of stated objectives to the highest ...
Proceedings of the International Conference on Industrial Engineering and Operations Management , 2019
This research focuses on the performance comparison of real-coded Genetic Algorithms (GA) and Bio... more This research focuses on the performance comparison of real-coded Genetic Algorithms (GA) and Biogeography-based Optimization (BBO) algorithms. Specifically, it takes three modified versions of the original algorithms made suitable for continuous operations (real-coded) – the standard real-coded GA (SRCGA), the real-coded GA with mathematical projection (RCGA-P) and the real coded-biogeographybased optimization algorithm (RCBBO); then conducts a performance-based comparison of these three with respect to convergence, speed and robustness criteria. This comparison was done using 52 standard optimization benchmark problems over four, ten and twenty dimensions. Results show that overall, SRCGA outperforms the others for speed while RCGA-P was the most robust of the three. The major value-add in performance of RCBBO was mainly from speed as in two dimensions, it delivers better speed than the two real-coded GA
Many Nigerians suffer from end stage kidney disease and require some form of renal replacement th... more Many Nigerians suffer from end stage kidney disease and require some form of renal replacement therapy (either dialysis or kidney transplantation) to sustain life. More than 50 parameters may be monitored while providing a kidney dialysis treatment. This work explored and analyzed the massive data generated for several years from the kidney patients in the University College Hospital (UCH), Ibadan using data mining technique. This is done by using Artificial Neural Network technique to select the input variables,
weight, and connectivity structure to determine optimal network topology and to train the system for learning. This helps to determine the features that are predictive of a patient life expectancy, detect the existence of renal failure in a patient, and to predict kidney dialysis survival. This work thus provides Physicians with an instrument that can automatically assess the dialysis service performance and support better understanding of the evaluation results.
"Genetic algorithms are efficient global optimizers, but they are weak in performing fine grained... more "Genetic algorithms are efficient global optimizers, but they are weak in performing fine grained local searches. In this paper, the local search capability of genetic algorithm is improved by hybridizing real coded genetic algorithm with ‘uniform random’ local search to form a hybrid real coded genetic algorithm termed ‘RCGAu’. The incorporated local technique is applied to all newly created offspring so that each offspring solution is given the opportunity to effectively search its local neighborhood for the best local optimum. Numerical experiments show that the performance of RCGA is remarkably improved by the uniform random local search technique."
Proceeding GECCO '13 Companion Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion
In this paper, a real-coded genetic algorithm (RCGA) which incorporates an exploratory search mec... more In this paper, a real-coded genetic algorithm (RCGA) which incorporates an exploratory search mechanism based on vector projection termed projection-based RCGA (PRCGA) is benchmarked on the noisefree BBOB 2013 testbed. It is an enhanced version of RCGA-P in [22, 23]. The projection operator incorporated in PRCGA shows promising exploratory search capability in some problem landscape. PRCGA is equipped with a multiple independent restart mechanism and a stagnation alleviation mechanism. The maximum number of function evaluations (#FEs) for each test run is set to 105 times the problem dimension. PRCGA shows encouraging results on several problems in the low and moderate search dimensions. It is able to solve each type of problem with the dimension up to 40 with lower precision but not all the functions to the desired level of accuracy of 10-8 especially for high conditioning and multi-modal functions within the specified maximum #FEs.
In this paper, a set of new real-coded genetic algorithms (RCGAs) with local and global explorato... more In this paper, a set of new real-coded genetic algorithms (RCGAs) with local and global exploratory search capabilities are proposed. The search capabilities are based on the inclusion of a modified crossover (MC) procedure and a new global exploratory method in RCGA. The global exploratory method is based on vector projection while the MC procedure is based on a limited version of the pattern search method. These modifications are introduced to increase the efficiency and robustness of RCGAs through better local and global exploration of the search region. An experimental study of the new algorithms was carried out using a set of 57 test problems. Statistical analyses and comparisons of the newalgorithms with standard real-coded genetic algorithm (SRCGA) and some recent global optimization algorithms were carried out. Results obtained show that the modifications remarkably improve the performance of RCGAs across the test problems.
Purpose The purpose of this paper is to consider the problem of university lecture timetabling.... more Purpose The purpose of this paper is to consider the problem of university lecture timetabling. Timetabling deals with the problem of placing certain resources into a limited number of time slots, subject to given constraints, in order to satisfy a set of stated objectives to the highest ...
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Papers by Babatunde Sawyerr
weight, and connectivity structure to determine optimal network topology and to train the system for learning. This helps to determine the features that are predictive of a patient life expectancy, detect the existence of renal failure in a patient, and to predict kidney dialysis survival. This work thus provides Physicians with an instrument that can automatically assess the dialysis service performance and support better understanding of the evaluation results.
weight, and connectivity structure to determine optimal network topology and to train the system for learning. This helps to determine the features that are predictive of a patient life expectancy, detect the existence of renal failure in a patient, and to predict kidney dialysis survival. This work thus provides Physicians with an instrument that can automatically assess the dialysis service performance and support better understanding of the evaluation results.