scholarly journals Solving assignment problems via Quantum Computing: a case-study in train seating arrangement

2021 ◽  
Author(s):  
Ilaria Gioda ◽  
Davide Caputo ◽  
Edoardo Fadda ◽  
Daniele Manerba ◽  
Blanca Silva Fernández ◽  
...  
Keyword(s):  
Quantum Computing ◽  
Assignment Problems ◽  
Seating Arrangement

scholarly journals Construction and evaluation of gold standards for patent classification—A case study on quantum computing

2020 ◽  
Vol 61 ◽  
pp. 101961 ◽  
Author(s):  
Steve Harris ◽  
Anthony Trippe ◽  
David Challis ◽  
Nigel Swycher
Keyword(s):  
Quantum Computing ◽  
Patent Classification ◽  
Gold Standards

scholarly journals Rotational Diversity in Multi-Cycle Assignment Problems

2019 ◽  
Vol 33 ◽  
pp. 7724-7731
Author(s):  
Helge Spieker ◽  
Arnaud Gotlieb ◽  
Morten Mossige
Keyword(s):  
Assignment Problem ◽  
Profit Maximization ◽  
Test Case ◽  
Test Cases ◽  
Assignment Problems ◽  
Assignment Model ◽  
Multiple Cycles ◽  
Multiple Knapsack ◽  
Objective Value

In multi-cycle assignment problems with rotational diversity, a set of tasks has to be repeatedly assigned to a set of agents. Over multiple cycles, the goal is to achieve a high diversity of assignments from tasks to agents. At the same time, the assignments’ profit has to be maximized in each cycle. Due to changing availability of tasks and agents, planning ahead is infeasible and each cycle is an independent assignment problem but influenced by previous choices. We approach the multi-cycle assignment problem as a two-part problem: Profit maximization and rotation are combined into one objective value, and then solved as a General Assignment Problem. Rotational diversity is maintained with a single execution of the costly assignment model. Our simple, yet effective method is applicable to different domains and applications. Experiments show the applicability on a multi-cycle variant of the multiple knapsack problem and a real-world case study on the test case selection and assignment problem, an example from the software engineering domain, where test cases have to be distributed over compatible test machines.

scholarly journals QRev: migrating quantum code towards hybrid information systems

2021 ◽  
Author(s):  
Ricardo Pérez-Castillo ◽  
Luis Jiménez-Navajas ◽  
Mario Piattini
Keyword(s):  
Quantum Computing ◽  
Information Systems ◽  
Quantum Code ◽  
Model Driven ◽  
Computing Paradigm ◽  
Business Operations ◽  
Quantum Technology ◽  
Specific Quantum ◽  
Future Business

AbstractQuantum computing is now a reality, and its incomparable computational power has led companies to show a great interest in being able to work with quantum software in order to support part of their current and future business operations. However, the quantum computing paradigm differs significantly from its classical counterparts, which has brought about the need to revolutionise how the future software is designed, built, and operated in order to work with quantum computers. Since companies cannot discard all their current (and probably mission-critical) information systems, they must adapt their classical information systems to new specific quantum applications, thus evolving towards hybrid information systems. Unfortunately, there are no specific methods with which to deal with this challenge. We believe that reengineering, and more specifically, software modernisation using model-driven engineering principles, could be useful as regard migrating classical systems and existing quantum programs towards hybrid information systems. This paper, therefore, presents QRev, a reverse engineering tool that analyses quantum programs developed in Q# in order to identify its components and interrelationships, and then generates abstract models that can be used in software modernisation processes. The platform-independent models are generated according to the Knowledge Discovery Metamodel (KDM) standard. QRev is validated in a case study involving five quantum programs in order to demonstrate its effectiveness and scalability. The main implication of the study is that QRev can be used in order to attain KDM models, which can subsequently be employed to restructure or add new quantum functionality at a higher abstraction level, i.e. independently of the specific quantum technology.

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