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Full-Text Articles in Engineering
Vehicle Routing Problem With Stochastic Demand (Vrpsd): Optimisation By Neighbourhood Search Embedded Adaptive Ant Algorithm (Ns-Aaa), M Nagalakshmi, Mukul Tripathi, Nagesh Shukla, Manoj Tiwari
Vehicle Routing Problem With Stochastic Demand (Vrpsd): Optimisation By Neighbourhood Search Embedded Adaptive Ant Algorithm (Ns-Aaa), M Nagalakshmi, Mukul Tripathi, Nagesh Shukla, Manoj Tiwari
Nagesh Shukla
Taking into account the real world applications, this paper considers a vehicle routing problem with stochastic demand (VRPSD) in which the customer demand has been modelled as a stochastic variable. Considering the computational complexity of the problem and to enhance the algorithm performance, a neighbourhood search embedded adaptive ant algorithm (ns-AAA) is proposed as an improvement to the existing ant colony optimisation. The proposed metaheuristic adapts itself to maintain an adequate balance between exploitation and exploration throughout the run of the algorithm. The performance of the proposed methodology is benchmarked against a set of test instances that were generated using …
Optimal Sensor Distribution For Multi-Station Assembly Process Using Chaos-Embedded Fast-Simulated Annealing, N Shukla, M Tiwari, R Shankar
Optimal Sensor Distribution For Multi-Station Assembly Process Using Chaos-Embedded Fast-Simulated Annealing, N Shukla, M Tiwari, R Shankar
Nagesh Shukla
This paper presents a novel methodology for the allocation of sensors in multi-station assembly processes. It resolves two core issues pertaining to the determination of an optimal number of sensors to be employed and their best locations. To make the traditional approach more effective, the effect of noise on sensor placement is minimized by maximizing the determinant of the Fischer information matrix. A state-space approach is adopted to model the variation propagation pertaining to the transfer of parts in a given multi-station assembly process. Further, the objective function conceived is significant over other contributions with respect to adding the effect …
Multi Station Assembly Process And Determining The Optimal Sensor Placement Using Chaos Embedded Fast Simulated Annealing, Nagesh Shukla, Manoj Tiwari, Ravi Shankar
Multi Station Assembly Process And Determining The Optimal Sensor Placement Using Chaos Embedded Fast Simulated Annealing, Nagesh Shukla, Manoj Tiwari, Ravi Shankar
Nagesh Shukla
This paper presents a new methodology for allocation of sensors in Multi Station Assembly processes. It resolves two core issues i.e. determining the optimal number of sensors to be used and the best locations for each of sensors. The effect of noise on the sensor placement has been minimized by maximizing the determinant of Fisher information matrix. The paper conceives objective function that is significant over other contributions in respect of adding the effect of noise coupled with the sensor data. To optimize the proposed objective function, a new algorithm is developed that combines Chaotic sequences with traditional Evolutionary Fast …
Optimization Of System Reliability Using Chaos-Embedded Self-Organizing Hierarchical Particle Swarm Optimization, M Bachlaus, N Shukla, M Tiwari, R Shankar
Optimization Of System Reliability Using Chaos-Embedded Self-Organizing Hierarchical Particle Swarm Optimization, M Bachlaus, N Shukla, M Tiwari, R Shankar
Nagesh Shukla
This paper addresses a reliability optimization problem, where the motive is to select the best components for series and series-parallel systems such that system reliability becomes maximized while simultaneously minimizing the cost, weight, and volume. Previous formulation of the problem has implicit restrictions, i.e. it either maximizes system reliability or minimizes the cost. Thus, in order to give a realistic view to the model, a comprehensive objective function has been formulated by combining the normalized values of reliability, cost, weight, and volume. In this paper, a chaos-embedded hierarchical particle swarm optimization (CE-HPSO) algorithm has been proposed to solve the problems …