## Project Details

### Description

The increased global awareness on environmental issues necessitated to take actions for reducing energy consumptions and CO2 emissions. As one of the largest energy consumers, the manufacturing sector also tries hard for this objective. On the one hand, energy efficient equipment, machines and processes are being developed and on the other hand, better planning and scheduling methodologies are developed to utilize the available resources more efficiently. This project is related to the latter one, where we consider improving the energy efficiency in manufacturing by better utilization of the available resources. For this purpose, we consider one of the most common production systems, namely parallel machine systems. We consider energy minimization problem for two common variations of this system. The first alternative is the classical parallel machine case with the most general and realistic assumptions such as the unrelated machines and sequence dependent setup times. The problem is to schedule the jobs to be processed with the objective of minimizing the total energy consumption of the machines. In the second variation, we consider the use of a material handling robot to serve these parallel machines. The speed of the robot is assumed to be adjustable and the energy consumption of the robot depends on the robot move speed. Here, the problem is to determine the robot move sequence and together with their speeds to minimize the energy consumption of the robot. In both variations, we will consider the energy minimization objective together with maximization of the throughput rate. Therefore, bi- or multi-criteria optimization models will be developed. Since the problem is complex, heuristic/metaheuristic solution algorithms will be developed. Their performance will be evaluated with a computational study. The effect of considering energy objective together with the throughput objective will also be analyzed through a computational study.

### Layman's description

The increased global awareness on environmental issues necessitated to take actions for reducing energy consumptions and CO2 emissions. As one of the largest energy consumers, the manufacturing sector also tries hard for this objective. On the one hand, energy efficient equipment, machines and processes are being developed and on the other hand, better planning and scheduling methodologies are developed to utilize the available resources more efficiently. This project is related to the latter one, where we consider improving the energy efficiency in manufacturing by better utilization of the available resources. For this purpose, we consider one of the most common production systems, namely parallel machine systems. We consider energy minimization problem for two common variations of this system. The first alternative is the classical parallel machine case with the most general and realistic assumptions such as the unrelated machines and sequence dependent setup times. The problem is to schedule the jobs to be processed with the objective of minimizing the total energy consumption of the machines. In the second variation, we consider the use of a material handling robot to serve these parallel machines. The speed of the robot is assumed to be adjustable and the energy consumption of the robot depends on the robot move speed. Here, the problem is to determine the robot move sequence and together with their speeds to minimize the energy consumption of the robot. In both variations, we will consider the energy minimization objective together with maximization of the throughput rate. Therefore, bi- or multi-criteria optimization models will be developed. Since the problem is complex, heuristic/metaheuristic solution algorithms will be developed. Their performance will be evaluated with a computational study. The effect of considering energy objective together with the throughput objective will also be analyzed through a computational study.

Acronym | TTotP |
---|---|

Status | Not started |

### Keywords

- Scheduling
- Energy minimization
- bi-criteria optimization
- robotic cells
- parallel machines

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