This paper addresses the challenge of moving objects in a mobile wireless sensor network, considering deployment limited number nodes within predetermined area to provide coverage for traveling on trajectory. Because insufficient and sensing range sensors, entire object’s trajectory cannot be covered by all deployed sensors. To address this problem complete coverage, sensors must move from one ...

One of the main challenges in postdisaster management large transportation networks involves determination priority and level service recovery for each damaged asset network. Presently, application metaheuristic algorithms developing restoration programs is receiving increasing attention. These determine a good solution to minimize consequences extreme events on network study relatively short p...

In this study, we set the average taxi time of flight as the objective of the gate and runway assignment problem. We present a gate and runway combinatorial optimization model with several restrictions such as restrictions of gate and runway time, type of aircraft and service. We design a Discrete Particle Swarm Optimization (DPSO) algorithm to solve this problem. Inspired by the genetic algori...

This paper develops an efficient and clear insight view about the application of various PSO algorithms to the economic load dispatch problem with emission restrictions as the constraint. Solution acceleration techniques in the algorithm which enhance the speed and robustness of the algorithm are developed. The power and usefulness of the algorithm is demonstrated through its application to a t...

Particle swarm optimization (PSO) is a kind of evolutionary algorithm to find optimal solutions for continuous optimization problems. Updating kinetic equations for particle swarm optimization algorithm are improved to solve traveling salesman problem (TSP) based on problem characteristics and discrete variable. Those strategies which are named heuristic factor, reversion mutant and adaptive no...

This paper proposes a discrete particle swarm optimization (DPSO) for the solution of the shortest path problem (SPP). The proposed DPSO termed as DPSO_SPP adopts a new solution representation which incorporates a search decomposition procedure and random selection of priority value. The purpose of this representation is to reduce the searching space of the particles, leading to a better soluti...

The need to deduce interesting and valuable information from large, complex, information-rich data sets is common to many research fields. Rule discovery or rule mining uses a set of IF-THEN rules to classify a class or category in a comprehensible way. Besides the classical approaches, many rule mining approaches use biologicallyinspired algorithms such as evolutionary algorithms and swarm int...

In the recent work demonstrate that a person is ready to join a social group action if the particular activity is attractive, and if a number of close friend’s moreover also join the activity as companions. From the survey it shows with the intention of the interests of a person and the social rigidity between friends is able to be successfully derived and mined from social networking websites....

The potential collision between the ship and pipe piles of jacket structure brings huge risks to safety an offshore platform. Due their high energy-absorbing capacity, honeycomb structures have been widely used as impact protectors in various engineering applications. This paper proposes a data-driven intelligent approach for prediction response honeycomb-reinforced under collision. In proposed...

Offshore jacket-type towers are steel structures designed and constructed in marine environments for various purposes such as oil exploration and exploitation units, oceanographic research, and undersea testing. In this paper a newly developed meta-heuristic algorithm, namely Cyclical Parthenogenesis Algorithm (CPA), is utilized for sizing optimization of a jacket-type offshore structure. The a...