Energy-efficient rescheduling with time-of-use energy cost: Application of variable neighborhood search algorithm

Abstract

Energy-efficient scheduling has drawn wide attention in the last few decades from both academia and industry due to its significance in energy saving and environmental protection. However, dynamic disruptions in practical scenarios such as dynamic arrival of orders, release time of raw materials, and machine breakdown, make it challenging to find an energy-efficient scheduling scheme. In an effort to overcome this challenge, we propose a novel energy- efficient rescheduling model with Time-of-use (TOU) energy cost, where two energy costs in peak and off-peak periods for processing jobs are considered. The objective of this work is to minimize the total energy consumption of both the original and new arrival jobs without excessively disrupting the original jobs’ schedule. To solve this problem, we first analyze the characteristics and calculation of energy consumption. We then apply a variable neighborhood search algorithm (VNS) to obtain near-optimal solutions. To avoid invalid swapping operations in the existing swapping neighborhood structures, three novel swapping neighborhood structures are proposed in the VNS algorithm. Computational experiments are performed to show the effectiveness and efficiency of the proposed algorithm.