Truck Scheduling: A Case Study in the Automotive Sector

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Vydáno v:International Journal of Applied and Computational Mathematics vol. 10, no. 2 (Apr 2024), p. 71
Hlavní autor: de Oliveira, Caroline Maruchi
Další autoři: Kleina, Mariana, da Silva, Arinei Carlos Lindbeck
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Springer Nature B.V.
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100 1 |a de Oliveira, Caroline Maruchi  |u Federal University of Parana, Postgraduate Program in Production Engineering, Curitiba, Brazil (GRID:grid.20736.30) (ISNI:0000 0001 1941 472X) 
245 1 |a Truck Scheduling: A Case Study in the Automotive Sector 
260 |b Springer Nature B.V.  |c Apr 2024 
513 |a Case Study Journal Article 
520 3 |a Logistic companies face several problems in their services, leading to increased time and costs in their operations. These issues could be mitigated if decision-making were based on models that consider resource optimization and respect process constraints. An example of this problem is the queues generated by trucks at docks for loading and unloading materials in the automotive sector. Therefore, this work studies truck scheduling with the inclusion of forbidden time windows for breaks. The aim is to propose a mathematical model in order to minimize the time spent by drivers within companies and to present exact and approximate solutions with the use of Operational Research techniques and algorithms. Methods and algorithms that adapt to this type of problem were identified. Then, the mathematical model was developed, computationally implemented in the LINGO and Gurobi software, and validated according to the case study conditions. A metaheuristic based on the Simulated Annealing algorithm was implemented in Visual Basic for Applications language, and used as a form of approximate resolution for problems larger than the ones solved optimally. Computational experiments were conducted to evaluate the performance of the model and metaheuristic proposed. The GAP between the metaheuristic solution and the optimal solution is less than 4% for all problems tested. For larger problems, with more than 10 trucks and 5 docks, Gurobi optimization software is not able to find the optimal solution in a feasible time. However, the metaheuristic is able to find good solutions for bigger problems in a reasonable time. Therefore, results proved the performance of the mathematical model, indicating that truck scheduling is an important tool for automotive companies, as it can help to improve efficiency and productivity. 
653 |a Customer services 
653 |a Docks 
653 |a Performance evaluation 
653 |a Optimization 
653 |a Trucks 
653 |a Production planning 
653 |a Manufacturing 
653 |a Visual Basic for Applications 
653 |a Heuristic methods 
653 |a Case studies 
653 |a Factories 
653 |a Scheduling 
653 |a Automobile industry 
653 |a Decision making 
653 |a Algorithms 
653 |a Supply chains 
653 |a Literature reviews 
653 |a Windows (intervals) 
653 |a Simulated annealing 
653 |a Logistics 
653 |a Software 
700 1 |a Kleina, Mariana  |u Federal University of Parana, Postgraduate Program in Production Engineering, Curitiba, Brazil (GRID:grid.20736.30) (ISNI:0000 0001 1941 472X) 
700 1 |a da Silva, Arinei Carlos Lindbeck  |u Federal University of Parana, Postgraduate Program in Production Engineering, Curitiba, Brazil (GRID:grid.20736.30) (ISNI:0000 0001 1941 472X) 
773 0 |t International Journal of Applied and Computational Mathematics  |g vol. 10, no. 2 (Apr 2024), p. 71 
786 0 |d ProQuest  |t Science Database 
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