This paper presents a cumulative multi-niching genetic algorithm (CMN GA), designed to expedite optimization problems that have computationally-expensive multimodal objective functions. By never discarding individuals from the population, the CMN GA makes use of the information from every objective function evaluation as it explores the design space. A fitness-related population density control...

Transmission losses has effected in every developed & underdeveloped country, so every nation are trying to optimize this losses by various techniques. The trend of transmission losses in power industry throughout the world has motivates researches for developing algorithms and methodologies to trace transmission loss. This paper will present a new approach to minimize the losses through geneti...

Traffic congestion in urban areas is a very critical problem and increasing day-by-day due to increment in number of vehicles and un-expandable traffic infrastructure. Several intelligent control systems have been developed to deal with this issue. In this paper, a new lane bypass algorithm has been developed for route diversion resulting in smooth traffic flow on the urban road networks. Genet...

Solving NP hard problem like Travelling Salesman Problem (TSP) is a major challenge faced by analysts even though many techniques are available. Many versions of Genetic Algorithms are introduced by researchers to improve its performance in solving TSP. Clustering Genetic Algorithm (CGA) was recently introduced and this paper analyzes the results obtained by implementing it for TSP. It is obser...

Evolutionary Multi-Objective Optimization is becoming a hot research area and quite a few papers regarding these algorithms have been published. However the role of local search techniques has not been expanded adequately. This paper studies the role of a local search technique called 2opt for the Multi-Objective Travelling Salesman Problem (MOTSP). A new mutation operator called Jumping Gene (...

Hydro generation scheduling is a nonlinear programming problem. This paper describes the hydro generation scheduling problem constraints. The optimal hydro scheduling problem is formulated as a large scale linear programming algorithm and is solved using a commercially available linear programming package. The selected objective function requires minimization of demand and generation of a hydro...

A total of 1,576 adults between 18 and 95 years of age performed a battery of cognitive tests and the Connections version of the Trail Making Test twice, with an average interval between assessments of 2.5 years. Consistent with previous results, speed ability and fluid cognitive ability were strongly correlated with trail making performance. Neither speed nor fluid cognitive ability at the fir...

Genetic Algorithm which is based on the Darwinian principle of natural selection has been successfully applied to Berth allocation problem (BAP), which can decide the ships’ berthing position and berthing time at a container terminal. Considering the service priority, handing time deciding variables, safety clearance, as well as the berths’ physical conditions, a dynamic berth allocation with d...

Overbidding in second-price auctions (SPAs) has been shown to be persistent and associated with cognitive ability. We study experimentally what extent cross-game learning can reduce overbidding SPAs, taking into account skills. Employing an order-balanced design, we use first-price (FPAs) expose participants auction format which losses from high bids are more salient than SPAs. Experience FPAs ...