in this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. scheduling algorithms play an important role in grid computing, parallel tasks scheduling and sending them to appr...

In this paper multi objective optimization problem for partitioning process of VLSI circuit optimization is solved using IPO algorithm. The methodology used in this paper is based upon the dynamic of sliding motion along a frictionless inclined plane. In this work, modules and elements of the circuit are divided into two smaller parts (components) in order to minimize the cutsize and area imbal...

To investigate the varietal difference in sulfur use efficiency (SUE) and drought stress tolerance, Brassica napus 'Mosa' and 'Saturnin' were exposed to polyethylene glycol (PEG)-induced drought stress for 72 h. Direct quantification of S uptake, de novo synthesis of amino acids and proteins was performed by tracing (34)S. The responses of photosynthetic activity in relation to SUE were also ex...

Particle swarm optimization (PSO) has received increasing attention in solving multi-objective economic dispatch (ED) problems in power systems because of parallel computation, faster convergence, and easier implementation. This paper presents a detailed overview of multi-objective particle swarm optimization (MOPSO) and provides a comprehensive survey on its applications in power system econom...

Integrated production-distribution planning (PDP) is one of the most important approaches in supply chain networks. We consider a supply chain network (SCN) to consist of multi suppliers, plants, distribution centers (DCs), and retailers. A bi-objective mixed integer linear programming model for integrating production-distribution designed here aim to simultaneously minimize total net costs in ...

Reverse logistics, which is induced by various forms of used products and materials, has received growing attention throughout this decade. In a highly competitive environment, the service level is an important criterion for reverse logistics network design. However, most previous studies about product returns only focused on the total cost of the reverse logistics and neglected the service lev...

Abstract The integration of Internet Things devices onto the Blockchain implies an increase in transactions that occur on Blockchain, thus increasing storage requirements. A solution approach is to leverage cloud resources for storing blocks within chain. paper, therefore, proposes two solutions this problem. first being improved hybrid architecture design which uses containerization create a s...

Simulated annealing is a metaheuristic that balances exploration and exploitation to solve global optimization problems. However, deal with multi- many-objective problems, this balance needs be improved due diverse factors such as the number of objectives. To issue, work proposes MOSA/D, hybrid framework for multi-objective simulated based on decomposition evolutionary perturbation functions. A...

The Job Shop Scheduling Problem (JSSP) has enormous industrial applicability. This problem refers to a set of jobs that should be processed in specific order using machines. For the single-objective optimization JSSP problem, Simulated Annealing is among best algorithms. However, Multi-Objective (MOJSSP), these algorithms have barely been analyzed, and Threshold Accepting Algorithm not publishe...

A newmultiobjective particle swarm optimization (MOPSO) technique for environmental/economic dispatch (EED) problem is proposed in this paper. The proposed MOPSO technique evolves a multiobjective version of PSO by proposing redefinition of global best and local best individuals in multiobjective optimization domain. The proposedMOPSO technique has been implemented to solve the EED problemwith ...