The impact of incentive-based programmes on job-shop scheduling with variable machine speeds

Given the high demand for energy in the manufacturing industry and the increasing use of renewable but volatile energy sources, it becomes increasingly important to coordinate production and energy availability. With the help of incentive-based programmes, grid operators can incentivise consumers to adjust power demand in critical situations such that grid stability is not threatened. On the consumer side, energy-efficient scheduling models can be used to make energy consumption more flexible. This paper proposes a bi-objective job-shop scheduling problem with variable machine speeds that aims on minimising the total energy consumption and total weighted tardiness simultaneously. We use a genetic algorithm to solve the model and derive Pareto frontiers to analyse the trade-off between both conflicting objectives. We gain insights into how incentive-based programmes can be integrated into machine scheduling models and analyse the potential interdependencies and benefits that result from this integration.

Automated summary

This paper investigates the issue of energy demand and renewable energy usage increase in the manufacturing industry, and explores how production and energy supply can be coordinated through incentive-based programs and energy-efficient scheduling models. A bi-objective job-shop scheduling problem with variable machine speeds is solved using a genetic algorithm, and Pareto frontiers are derived to analyze the trade-off between total energy consumption and total weighted tardiness.