Minimizing total tardiness on one machine is NP-hard
Mathematics of Operations Research
A Multiple-Criterion Model for Machine Scheduling
Journal of Scheduling
Scheduling Problems with Two Competing Agents
Operations Research
A note on the scheduling with two families of jobs
Journal of Scheduling
Multi-agent scheduling on a single machine to minimize total weighted number of tardy jobs
Theoretical Computer Science
Mixed Criteria Packet Scheduling
AAIM '07 Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management
Two-Agent Scheduling with Linear Deteriorating Jobs on a Single Machine
COCOON '08 Proceedings of the 14th annual international conference on Computing and Combinatorics
Approximation algorithms for multi-agent scheduling to minimize total weighted completion time
Information Processing Letters
A Lagrangian approach to single-machine scheduling problems with two competing agents
Journal of Scheduling
Competitive Two-Agent Scheduling and Its Applications
Operations Research
Expert Systems with Applications: An International Journal
Branch-and-bound and simulated annealing algorithms for a two-agent scheduling problem
Expert Systems with Applications: An International Journal
A two-machine flowshop problem with two agents
Computers and Operations Research
Computers and Industrial Engineering
Simplified multi-objective genetic algorithms for stochastic job shop scheduling
Applied Soft Computing
Parallel genetic algorithm in bus route headway optimization
Applied Soft Computing
Solving job shop scheduling problem using a hybrid parallel micro genetic algorithm
Applied Soft Computing
Two-agent scheduling with learning consideration
Computers and Industrial Engineering
Solving a two-agent single-machine scheduling problem considering learning effect
Computers and Operations Research
Information Sciences: an International Journal
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Scheduling with two competing agents has drawn a lot of attention lately. However, it is assumed that all the jobs are available in the beginning in most of the research. In this paper, we study a single-machine problem in which jobs have different release times. The objective is to minimize the total tardiness of jobs from the first agent given that the maximum tardiness of jobs from the second agent does not exceed an upper bound. Three genetic algorithms are proposed to obtain the near-optimal solutions. Computational results show that the branch-and-bound algorithm could solve most of the problems with 16 jobs within a reasonable amount of time. In addition, it shows that the performance of the combined genetic algorithm is very good with mean error percentages of less than 0.2% for all the cases.