Geodesic
A JSSP Solution for Production Planning Optimization Combining Industrial Engineering and Evolutionary Algorithms
Computer Science and Information Systems, Tome 18 (2021) no. 1.

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A Job Shop Scheduling Problem (JSSP), where p processes and n jobs should be processed on m machines so that the total completion time is minimal, is a well-known problem with many industrial applications. Many researchers focus on the JSSP classification and algorithms that address the different JSSP classes. In this research work, the production times, a very well-known theme covered in Industrial Engineering (IE), are integrated into an Evolutionary Algorithm (EA) to solve real-world JSSP problems. Since a drawback of classical IE is a manual determination of the technological times, an Internet of Things (IoT) architecture is proposed as a possible solution.
Keywords: JSSP, genetic algorithms, industrial engineering, internet of things 
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     author = {Sa\v{s}o Sr\v{s}en and Marjan Mernik},
     title = {A {JSSP} {Solution} for {Production} {Planning} {Optimization} {Combining} {Industrial} {Engineering} and {Evolutionary} {Algorithms}},
     journal = {Computer Science and Information Systems},
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Sašo Sršen; Marjan Mernik. A JSSP Solution for Production Planning Optimization Combining Industrial Engineering and Evolutionary Algorithms. Computer Science and Information Systems, Tome 18 (2021) no. 1. http://geodesic.mathdoc.fr/item/CSIS_2021_18_1_a17/