Reducing domains for search in CLP(FD) and its application to job-shop scheduling

Goltz, Hans-Joachim

doi:10.1007/3-540-60299-2_33

Cited by 8 publications

(1 citation statement)

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“…transition times were handled on algorithmic level using a new approach described in [16]. These filtering algorithms are pruning the search space and are used together with a depth-first tree-search called domain reduction [28] for minimizing the makespan. The chosen algorithms also support optional activities so that they are applicable in the case where transport tasks can be performed by more than AGV.…”

Section: Solving the Extended Jsp With Agv Transport Using Constraint...mentioning

confidence: 99%

Solving the Extended Job Shop Scheduling Problem with AGVs -- Classical and Quantum Approaches

Geitz¹,

Grozea²,

Steigerwald³

et al. 2021

Preprint

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The subject of Job Scheduling Optimisation (JSO) deals with the scheduling of jobs in an organization, so that the single working steps are optimally organized regarding the postulated targets. In this paper a use case is provided which deals with a sub-aspect of JSO, the Job Shop Scheduling Problem (JSSP or JSP). As many optimization problems JSSP is NP-complete, which means the complexity increases with every node in the system exponentially. The goal of the use case is to show how to create an optimized duty rooster for certain workpieces in a flexible organized machinery, combined with an Autonomous Ground Vehicle (AGV), using Constraint Programming (CP) and Quantum Computing (QC) alternatively. The results of a classical solution based on CP and on a Quantum Annealing model are presented and discussed. All presented results have been elaborated in the research project PlanQK.

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Section: Solving the Extended Jsp With Agv Transport Using Constraint...mentioning

confidence: 99%