This paper proposes a novel multi-objective ant colony system (MOACS) approach to solve the cooperative task allocation problem of multi-robot systems. The is formulated as multiple traveling salesman (MTSP). objectives are minimize total and maximum cost robotic vehicles so that workload each vehicle could be balanced. time matrices salesmen different asymmetric due flight speeds executing tas...

We present a new iterative mathematical model for calculating the average bandwidth assigned to traffic flows using a Weighted Round Robin with Priority queuing (WRRPQ) scheduler with both strict and rate controlled priority in IP based NGN networks. The bandwidth assignment estimation is based on the average packet length, link speed and the arrival rate. We prove the model outcome with exampl...

This study compares a number of selection regimes for the choosing of global best (gbest) and personal best (pbest) for swarm members in multi-objective particle swarm optimisation (MOPSO). Two distinct gbest selection techniques are shown to exist in the literature, those that do not restrict the selection of archive members and those with ‘distance’ based gbest selection techniques. Theoretic...

In this article we describe a novel Particle Swarm Optimization (PSO) approach to multi-objective optimization (MOO), called Time Variant Multi-Objective Particle Swarm Optimization (TV-MOPSO). TV-MOPSO is made adaptive in nature by allowing its vital parameters (viz., inertia weight and acceleration coefficients) to change with iterations. This adaptiveness helps the algorithm to explore the s...

The time-cost trade-off problem is a known bi-objective problem in the field of project management. Recently, a new parameter, the quality of the project has been added to previously considered time and cost parameters. The main specification of the time-cost trade-off problem is discretization of the decision space to limited and accountable decision variables. In this situation the efficiency...

The accurate classification of reservoir recovery factor is dampened by irregularities such as noisy and high-dimensional features associated with the measurements or characterization. These irregularities, especially a larger number features, make it difficult to perform factor, generated are usually heterogeneous. Consequently, imperative select relevant while preserving amplifying accuracy. ...

The application of multi objective model predictive control approaches is significantly limited with computation time associated with optimization algorithms. Metaheuristics are general purpose heuristics that have been successfully used in solving difficult optimization problems in a reasonable computation time. In this work , we use and compare two multi objective metaheuristics, Multi-Object...