1、绿色调度Green Scheduling
1.introduction
With the current increase in environmental awareness, green manufacturing research and application attracts considerable attention. The aim of green manufacturing is to minimize environmental dam-age and energy waste while guaranteeing the quality and function of products and improving the profit of manufacturing enterprises. It comprehensively considers environmental impacts and re-source efficiency to ensure economic and social benefits and the sustainability of industrial enter-prises. New manufacturing technologies and initiatives, such as digital manufacturing, additive manufacturing, smart manufacturing, and Internet of Things, provide new opportunities for green manufacturing, but also add complexity. As a significant part of green manufacturing, green sched-uling is a special category of shop and production scheduling problems where energy savings, re-source consumption reduction, and emission reduction are considered. Efficient green scheduling can provide significant benefits in both reduced costs and lessened environmental impact.
In recent decades, increases in the price and demand for fossil energy and the rising problem of global climate change have resulted in greater efforts directed towards minimizing energy and re-source consumption. According to the US Energy Information Administration, the industrial sector accounts for one-half of the world’s total energy consumption, which has almost been doubled over the last 60 years. In China since 1978, the industrial sector contributes about 40% of GDP, but con-sumes 67.9% of total national energy and emits 83.1% of total national carbon dioxide. However, most of the existing work on reducing energy consumption only focuses on developing more energy efficient machines or processes, instead of improving the operational process. At Toyota Motor Corporation, recent research shows that more than 85% of energy is consumed by non-machining operations, which are not directly related to the actual production of parts. To tackle this issue, more attention should be paid to developing efficient operational methods to implement a significant re-duction of energy.
This Special Volume (SV) aims to address green scheduling problems and explore different ap-proaches for energy savings and emission reductions. Up until now, the existing studies about green scheduling only considered a few simple problem characteristics, such as a single machine, flow shop scheduling, and so on. Complex constraints, including multiple resource constraints, flexible scheduling, and uncertainty situations should also be considered for the practical application of green scheduling. In addition to energy consumption and emission problems related to machine op-erations, design, packing, transportation and logistics, and recycling procedures should also embody the concept of “green scheduling.” Although green scheduling has become a research hotspot in the field of job scheduling, its practical applications are still limited. Advanced theoretical results have not yet been verified and applied to actual systems.
2. Topical areas
Theme 1: Green scheduling problems and its extensions
Most of the existing studies on green scheduling are aimed at traditional workshop scheduling problems, such as single machines, parallel machines, and so on, which is relatively simple. Green scheduling problems are faced by various industries. Several complex situations, such as multiple resource constraints, machine failures, cooperative manufacturing, and online scheduling can be studied to more accurately model practical applications. Moreover, models and calculations of en-ergy-saving measures are also very important to realize energy savings and emission reductions in terms of different specific applications. With this in mind, the following research ideas are wel-comed:
• Research review on green scheduling,（研究工作01）
• Definition and formulation of novel green scheduling problems, especially ones considering new manufacturing technologies, such as smart manufacturing, additive manufacturing, digital manufacturing, Internet of Things, new energy for manufacturing, etc., and business operations beyond shop floors.（研究工作02）
• Benchmark problem（基准问题） research of green scheduling systems.（研究工作03）
Theme 2: Algorithms
To satisfy the requirements of both economic and energy-saving measures, the green schedul-ing problem is typically modeled as a multi-objective optimization problem. This multiple objective problem requires a high-efficiency search capability in a decision-variable space and good equilib-rium or collaborative capabilities in the objective space for the solving algorithm. On the other hand, the complexity, the effectiveness, and the sensitivity analysis of multi-objective optimization algo-rithms should be considered, as well as some special techniques such as pareto dominance strategies, constraint satisfaction methods, analytic hierarchy processes, and so on. With this concern, the fol-lowing research ideas are encouraged:
• Algorithms for green manufacturing resource planning（研究工作04）
• Algorithms for green supply chain design and optimization（研究工作05）
• Algorithms for green manufacturing（研究工作06）
• Algorithms for smart green manufacturing systems（研究工作07）
• Algorithms for unmanned green manufacturing systems（研究工作08）
• Multi-objective optimization algorithms for green manufacturing systems（研究工作09）
• Dynamic optimization algorithms for green manufacturing systems（研究工作10）
• Uncertain optimization algorithms for green manufacturing systems（研究工作11）
• Memetic algorithms（文化基因算法） for green manufacturing（研究工作12）
Theme 3: Applications
Although some work has been conducted on green scheduling, few have adapted the academic results into practical applications. It is important to build more practical models and to specifically develop implementable algorithms for green scheduling problems by deeply analyzing the nature of different problem characteristics, such as:
• Memetic algorithms for manufacturing in practical systems（研究工作13）
• A future vision for green scheduling systems（研究工作14）
• Application practices of green scheduling systems（研究工作15）
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