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Pareto optimal algorithms for minimizing total (weighted) completion time and maximum cost on a single machine.
1College of Computer Science and Technology, Shandong Technology and Business University, Yantai 264005, China.
This study presents efficient algorithms for the Pareto scheduling problem, aiming to minimize total weighted completion time and maximum cost on a single machine. The research focuses on specific scenarios where processing times, release dates, and weights are equal or arbitrary.
Area of Science:
- Operations Research
- Computer Science
- Algorithm Design
Background:
- The Pareto scheduling problem on a single machine is known to be strongly NP-hard.
- Minimizing total weighted completion time and maximum cost simultaneously presents significant computational challenges.
Purpose of the Study:
- To develop efficient algorithms for the Pareto scheduling problem.
- To address the NP-hard nature of the problem by providing polynomial-time solutions for specific cases.
Main Methods:
- The study employs algorithmic approaches to solve the Pareto scheduling problem.
- Focus is placed on developing algorithms with a running time complexity of O(n^3).
Main Results:
- Algorithms are presented for three distinct cases of the Pareto scheduling problem.
- These cases involve variations in processing times, release dates, and weights, including arbitrary and equal parameters.
Conclusions:
- The research provides effective $O(n^3)$ algorithms for specific instances of the strongly NP-hard Pareto scheduling problem.
- These findings contribute to the efficient solution of complex scheduling problems in operations research and computer science.
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