What question did this study set out to answer?

The aim is to develop a genetic algorithm that ensures feasible solutions in blocking job shop scheduling problems.

February 5, 2026AlgorithmsOpen Access

Evolutionary Optimization for Job Shop Scheduling with Blocking: A Genetic Algorithm Approach

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Demonstrates a genetic algorithm minimizes makespan in job shop scheduling, indicating improved solution quality.

The aim is to develop a genetic algorithm that ensures feasible solutions in blocking job shop scheduling problems.
Developed a genetic algorithm focused on the feasible solution space
Minimized the makespan as the objective function
Included an assignment operator to enhance population diversity
Tested the algorithm on Lawrence benchmark problems
Achieved solutions that outperform known makespan values for benchmark problems
No specific factors significantly influenced solution quality
Runtime varied from 20 s for smaller instances to 600 s for larger instances

VALENCIA et al. (2026) studied this question.

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