This paper presents a systematic procedure for the optimization of machining parameters such as cutting speed, feed rate, nose radius, edge radius, and rake angle to reduce specific material removal energy and improve energy efficiency in the hard turning of AISI 4140 steel. A simulation approach was applied in conjunction with the design of experiment (DOE), mathematical approximation with a m...

This paper presents the application of modified form of Particle Swarm Optimization as an optimization technique to the reconfiguration of electric distribution systems. The intended reconfiguration is an optimization and decision-making process which considers the maximization of the number of loads supplied associated to the minimization of the number of closed switches. A novel selection reg...

Industrial hazardous materials (hazmat) are byproduct of industrial production and include hazardous goods, such as flammable, toxic and corrosive materials that pose a risk to the environment.Hazardous waste management includes collection, transportation, treatment, recycling and disposal of industrial hazardous material in an organized manner. With the increasing industrialization of countrie...

to answer challenge of targeted and controlled drug release in oral delivery various materials were studied by different methods. in the present paper, controlled metal based drug (pd(ii) complex) release manner of β‑lactoglobulin (β-lg) nanoparticles was investigated using mathematical drug release model in order to design and production of a new oral drug delivery system for gastrointestinal ...

In this research, a hierarchical location-allocation problem is modeled in a queue framework. The queue model is considered as M/M/1/k, in which system capacity is finite, equals to k. This is the main contribution of the current research. Customer's enters to the system in order to find the service according to a Poisson. In this problem, the hierarchical location-allocation model is considere...

Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly ...

In this paper, we illustrate a novel optimization approach based on Multi-objective Particle Swarm Optimization (MOPSO) and Fuzzy Ant Colony Optimization (FACO). The basic idea is to combine these two techniques using the best particle of the Fuzzy Ant algorithm and integrate it as the best local Particle Swarm Optimization (PSO), to formulate a new approach called hybrid MOPSO with FACO (H-MOP...

Due to limited financial resources and high costs of infrastructure projects, project stakeholders seek gain maximum profits with optimal resource utilization as well cost time minimization. Therefore, this study presents a multi-mode resource-constrained scheduling model considering the uncertain parameters together goals maximizing net present value minimizing usage fluctuation. Also, assumpt...