Scheduling Problems in Sustainability

Dear Colleagues,

Scheduling problems belong to operation levels that impact daily efficiency profoundly in industry. They manifest themselves as form-of-production scheduling problems, nurse scheduling problems, project scheduling problems, timetable scheduling problems, and so on. Researchers may consider the minimization of the earliness, tardiness, makespan, the number of people, and so forth. If the number of the objective function is more than one, it becomes a bi-objective or a multi-objective problem. These smaller scheduling problems could be solved using exact algorithms, such as the branch-and-bound algorithm, dynamic programming, or mixed integer linear programming. When we deal with larger scheduling problems, in particular, the NP-Hard ones, some popular meta-heuristics, such as the Genetic Algorithm, Ant Colony Optimization, discrete particle swarm optimization, and tabu search.

Even though scheduling problems have been studied extensively, increasing concern about green scheduling is critical for enterprises. For example, carbon dioxide emissions during peak hours are higher than during off-peak hours in some countries. Manufacturers could process orders with higher electricity consumption outside of peak hours if the manufacturing environment applied time-of-use tariff (TOU). This effort could reduce the carbon footprint in the supply chain. Moreover, the unit costs during the off-peak and the mid-peak hours are both less than during peak hours. Operational level planning using scheduling is the most effective way to reduce energy costs, as well as sustainability considerations.

As a result, this Special Issue plans to call for papers addressing sustainable scheduling, and their applications to manufacturing, the service industry, and the medical environment, as well as to practicing managers/engineers. This Special Issue features a balance between new sustainability scheduling problems and state-of-the-art algorithms. This Special Issue also provides a forum for researchers and practitioners to review and distribute essential research papers on sustainable scheduling and their applications, and to identify critical problems for further developments.

Dr. Shih-Hsin Chen
Guest Editor

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