Priority rules for job shops with weighted tardiness costs
Management Science
Computers and Operations Research
Scheduling Computer and Manufacturing Processes
Scheduling Computer and Manufacturing Processes
Scheduling unrelated parallel machines to minimize total weighted tardiness
Computers and Operations Research
Evaluation of uncertainty on scheduling algorithms in printed wiring board manufacturing
Evaluation of uncertainty on scheduling algorithms in printed wiring board manufacturing
Computers and Operations Research
Parallel machine total tardiness scheduling with a new hybrid metaheuristic approach
Computers and Operations Research
Computers and Industrial Engineering
Computers and Operations Research
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
Engineering Applications of Artificial Intelligence
Journal of Intelligent Manufacturing
A comparison of mip-based decomposition techniques and VNS approaches for batch scheduling problems
Winter Simulation Conference
A variable neighbourhood search algorithm for job shop scheduling problems
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
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In this paper, we study a planning and scheduling problem for unrelated parallel machines. There are n jobs that have to be assigned and sequenced on m unrelated parallel machines. Each job has a weight that represents the priority of the corresponding customer order, a given due date, and a release date. An Automated Guided Vehicle is used to transport at maximum Load max jobs into a storage space in front of the machines in a given period of time. We consider t max consecutive periods. We are interested in minimizing the total weighted tardiness of the jobs across the periods. This measure is important when we are interested in a good on-time delivery performance. We present an appropriate mixed integer program. To solve this NP-hard problem, we develop a heuristic methodology based on decomposition and variable neighborhood search (VNS). The proposed approaches are assessed using randomly generated problem instances. We compare them with a simple heuristic based on decomposition and list scheduling using the Apparent Tardiness Cost dispatching rule. The results demonstrate that the heuristic approach based on VNS performs comparably to the mixed integer program while having reasonable solution times and outperforms the simple heuristic and a genetic algorithm (GA) from previous research.