The design and applications of the african buffalo algorithm for general optimization problems

Optimization, basically, is the economics of science. It is concerned with the need to maximize profit and minimize cost in terms of time and resources needed to execute a given project in any field of human endeavor. There have been several scientific investigations in the past several decades on discovering effective and efficient algorithms to providing solutions to the optimization needs of mankind leading to the development of deterministic algorithms that provide exact solutions to optimization problems. In the past five decades, however, the attention of scientists has shifted from the deterministic algorithms to the stochastic ones since the latter have proven to be more robust and efficient, even though they do not guarantee exact solutions. Some of the successfully designed stochastic algorithms include Simulated Annealing, Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, Bee Colony Optimization, Artificial Bee Colony Optimization, Firefly Optimization etc. A critical look at these ‘efficient’ stochastic algorithms reveals the need for improvements in the areas of effectiveness, the number of several parameters used, premature convergence, ability to search diverse landscapes and complex implementation strategies. The African Buffalo Optimization (ABO), which is inspired by the herd management, communication and successful grazing cultures of the African buffalos, is designed to attempt solutions to the observed shortcomings of the existing stochastic optimization algorithms. Through several experimental procedures, the ABO was used to successfully solve benchmark optimization problems in mono-modal and multimodal, constrained and unconstrained, separable and non-separable search landscapes with competitive outcomes. Moreover, the ABO algorithm was applied to solve over 100 out of the 118 benchmark symmetric and all the asymmetric travelling salesman’s problems available in TSPLIB95. Based on the successful experimentation with the novel algorithm, it is safe to conclude that the ABO is a worthy contribution to the scientific literature

African Buffalo Optimization Algorithm Based T-Way Test Suite Generation Strategy for Electronic-Payment Transactions

The use of meta-heuristics in Combinatorial Interaction Testing (CIT) is becoming more and more popular due to their effectiveness and efficiency over the traditional methods espe-cially in authenticating electronic payment (e-payment) transactions. Concomitantly, over the past two decades, there has been a rise both in the development of metaheuristics and their application to diverse theoretical and practical areas including CIT in e-payments. In the implementation of t-way strategies (the t is used to represent the interaction strength), mixed results have been reported; some very exciting but, in other cases, the performance of metaheuristics has been, to say the least, below par. This mixed trend has led many re-searchers to explore alternate ways of improving the effectiveness and efficiency of me-taheuristics in CIT, hence this study. It must be emphasized, however, that available litera-ture indicates that no particular metaheuristic testing strategy has had consistent superior performance over the others in diverse testing environments and configurations. The need for effectiveness, therefore, necessitates the need for algorithm hybridization to deploy only the component parts of algorithms that have been proven to enhance overall search capa-bilities while at the same time eliminating the demerits of particular algorithms in the hybrid-ization procedure. In this paper, therefore, a hybrid variant of the African Buffalo Optimi-zation (ABO) algorithm is proposed for CIT. Four hybrid variants of the ABO are proposed through a deliberate improvement of the ABO with four algorithmic components. Experi-mental procedures indicate that the hybridization of the ABO with these algorithmic com-ponents led to faster convergence and greater effectiveness superior to the outcomes of existing techniques, thereby placing the algorithm among the best when compared with other methods/techniques

Swarm Intelligence Optimization Algorithms: A Review

Swarm Intelligence, of late, has gradually become an exciting area of research interest to many researchers in science and engineering. The primary reason for this interest is because swarm intelligence exploits the miraculous cum harmonious working of nature in ensuring order, preservation, conservation, longevity and sustenance of plants and animals in the ecosystem. As a result, researchers that believe that mimicking nature is key to solving diverse problems in engineering, technology and science has developed a number of swarm intelligence techniques. This paper presents a review of some recently developed swarm intelligence algorithms that have been successfully applied to solve a number of optimization problems with special emphasis on their application areas, strengths and observable weaknesses. This study aims to assist researchers in their choice of algorithm to solve optimization problems

"Live Better Where You Are": Home Improvement And The Rhetoric Of Renewal In The Postwar United States

While sinuous rows of new suburban ramblers remain the predominant symbol of post-World War II housing in the United States, the upgrading of existing homes was an equally essential component of the era's popular and building culture. Businesses, government agencies, academia, mass media, designers, and homeowners promoted postwar home improvement-sometimes in collaboration, often in competition for market share, consumer dollars, and professional authority. Negotiating realignments of expertise, these groups saw renewal as a national imperative, a moral virtue, and social reward. They reinterpreted traditional notions of the home as symbol of stability and security, not through timeless permanence but through perpetual change. This study examines residential architecture as a temporal space, repeatedly reconfigured as a vehicle for self-expression and in response to shifting cultural priorities. It argues that home improvement, marketed and advertised, embraced and co-opted, drew rhetorical potency from established American attitudes toward personal reinvention and a privileging of the new. The dissertation does not attempt to offer a complete history of postwar home improvement. Rather, it identifies specific episodes and interpretive lenses that offer insights into the depth and breadth of postwar remodeling activities and the ways in which a nation's culture can provide a rhetorical foundation for reshaping its built environment

1995-1997 Undergraduate Catalog

1995-1997 undergraduate catalog of Morehead State University

1990-1991 Undergraduate Catalog

1990-1991 undergraduate catalog of Morehead State University

1994-1995 Undergraduate Catalog

1994-1995 undergraduate catalog of Morehead State University

1991-1992 Undergraduate Catalog

1991-1992 undergraduate catalog of Morehead State University