Search

In recent years there has been increased concern on energy efficiency of industries. Since the scheduling problems in the shop floors are directly related to the energy consumption, an appropriate way to improve energy efficiency in industrial plants is to develop effective scheduling strategies. Hence, the aim of this paper is to design an energy-efficient scheduling in a shop floor industrial environment, i.e., flexible job-shop scheduling problem (FJSP). To this end, a multi-objective optimization model is developed with three objective functions: (i) minimizing total completion time, (ii) maximizing the total availability of the system, and (iii) minimizing total energy cost of both production and maintenance operations in the FJSP. To cope with this multi-objective optimization problem, an enhanced evolutionary algorithm incorporated with the global criterion, as a multi-objective handling technique, is proposed and then performance evaluation is performed based on an extensive numerical analysis. [ABSTRACT FROM AUTHOR]

Natural gas is usually transported by pipeline networks. This paper presents a multi-objective optimization model in optimizing the operation of natural gas pipeline networks. A mathematical model is established for different network configurations, namely linear, branch and looped topologies. Two conflicting objectives, power consumption minimization and gas delivery flow rate maximization, are considered subjected to pipeline and compressor constraints. The decision variables are the pressure at the nodes and the rotational speed of the compressors. A set of constraints is developed based on gas flow equations and compressors operating conditions. Due to the nonlinearity of the constraints and the objective, the developed model is a Nonlinear Programming problem. The optimization of the models is performed with NSGA-II algorithm. The solution obtained is a set of Pareto optimal points from which a decision maker can select a specific preferred solution. Sensitivity analysis was performed to determine the impact of parameter changes. [ABSTRACT FROM AUTHOR]