Energy Efficient Network Manufacturing System Using Controlled Elitist Non-dominated Sorting Genetic Algorithm

Recent manufacturing systems did not just confine to optimal utilization of resources due to the global stance on strict environmental regimes. Collaborative effort to achieve sustainable practices in the decentralized manufacturing environment is a new complex problem. In this paper, with a networked manufacturing system we try to achieve both traditional as well as sustainable parameters by optimizing the performances such as makespan, machine utilization, and energy consumption. Thereafter, we formulate the problem as a mixed-integer non-linear programming (MINLP) model. To handle this NP-hard problem and to find the optimal solutions a Controlled elitist non-dominated sorting genetic algorithm (CE-NSGA-II) has been adopted. Finally, the results are analyzed with different scenarios to prove the proposed approach validation.