OPTIMAL SCHEDULING OF GAS STATION ATTENDANT USING INTEGER LINEAR PROGRAMMING METHOD (STUDY ON GAS STATION 44.574.03 JONGGRANGAN KLATEN)

Authors

  • Dwi Hastjarja Kustijana B Management Study Program, Faculty of Economics and Business, Universitas Sebelas Maret, Indonesia
  • Daniel Jordy Kriswandi Management Study Program, Faculty of Economics and Business, Universitas Sebelas Maret, Indonesia
  • Darmanto Darmanto ITB AAS Indonesia, Indonesia

DOI:

https://doi.org/10.29040/ijebar.v7i3.10411

Abstract

Gas Station (SPBU) generally serve the needs of consumers 24 hours a day. The problem of employee scheduling is a problem that is often faced by companies because scheduling that is not optimal can cause wasted costs. The rules applied by the gas station company and the limited number of employees are the determining factors in the preparation of the employee schedule. This scheduling problem can be applied to the Integer Linear Programming modeling. Integer Linear Programming is a linear programming calculation model with a linear objective function, linear constraints function, and integer variables. This employee scheduling problem is solved using the Integer Linear Programming method with the aim of minimizing employee salary costs without reducing the number of employees and not ignoring the rules and or constraints set by the company. This study discusses the problem formulation of gas station employee scheduling in the form of Integer Linear Programming in a case study at SPBU 44574.03 Jonggrangan Klaten. Mathematical formulations and models were completed with the help of the LINGO 8.0 computer application. Keywords: gas stations, employee scheduling, integer linear programming, minimum cost

References

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Published

2023-08-26

How to Cite

Kustijana B, D. H., Kriswandi, D. J., & Darmanto, D. (2023). OPTIMAL SCHEDULING OF GAS STATION ATTENDANT USING INTEGER LINEAR PROGRAMMING METHOD (STUDY ON GAS STATION 44.574.03 JONGGRANGAN KLATEN). International Journal of Economics, Business and Accounting Research (IJEBAR), 7(3). https://doi.org/10.29040/ijebar.v7i3.10411

Issue

Vol. 7 No. 3 (2023): IJEBAR, VOL. 07 ISSUE 03, SEPTEMBER 2023

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