NP-hard problems are not believed to be exactly solvable through general polynomial time algorithms. Hybrid quantum-classical algorithms address such combinatorial have been of great interest in the past few years. Such heuristic nature and aim obtain an approximate solution. Significant improvements computational and/or ability treat large some principal promises quantum computing this regard. The hardware, however, is still its infancy current noisy intermediate-scale (NISQ) computers able...

This article studies the effect of partial coverage to extend lifetime wireless sensor networks and introduces a hybrid exact solution strategy that efficiently maximizes network lifetime. We consider set sensors used provide discrete targets transfer information sink node via multi‐hop communication. An active has one two roles: it is source when senses transfers data; relay if only data. Network extended through use covers representing role allocation topology. A column generation identify...

A disruption management problem for commercial airlines has been presented by Amadeus the ROADEF 2009 Challenge, an international competition organised French Operational Research and Decision Support Society (ROADEF). This paper presents this industrial large scale optimisation underlines its difficulties compared to previously tackled problems in area. We review most prominent methods proposed candidates provide official results participant ranking. Last, as lessons learned from...

This paper deals with the Generalised Workforce Scheduling and Routing Problem (GWSRP) where 9 temporal constraints ensuring visit dependencies are all together taken into account customer worker's quality of service consideration. A Constraint-Programming based Decomposition Method (CPDM) is proposed, firstly on a relaxation coordination column generation, secondly an iterative insertion constraint by programming solver. Numerical experiments achieved huge instances derived from WSRP...

The automated generation of models that conform to a given meta-model is an important challenge in Model Driven Engineering, as well for model transformation testing, designing and exploring new metamodels.Amongst the main issues, we are mainly concerned by scalability, flexibility reasonable computing time.This paper presents approach generation, which relies on Constraint Programming.After translation into CSP, our software generates this metamodel, using Solver.Our also includes most...

NP-hard problems are not believed to be exactly solvable through general polynomial time algorithms. Hybrid quantum-classical algorithms address such combinatorial have been of great interest in the past few years. Such heuristic nature and aim obtain an approximate solution. Significant improvements computational and/or ability treat large some principal promises quantum computing this regard. The hardware, however, is still its infancy current Noisy Intermediate Scale Quantum (NISQ)...

Grover search is currently one of the main approaches to obtain quantum speed-ups for combinatorial optimization problems.The combination Quantum Minimum Finding (obtained from search) with dynamic programming has proved particularly efficient improve worst-case complexity several NP-hard problems.Specifically, these problems, classical (ignoring polynomial factors) in O * ( ) can be reduced by a bounded-error hybrid quantumclassical algorithm < .In this paper, we extend resulting three...

Disposing of relevant and realistic datasets is a difficult challenge in many areas, for benchmarking or testing purpose.Datasets may contain complexly structured data such as graphs models, obtaining kind sometimes expensive available benchmarks are not they should be.In this paper we propose model-driven approach based on probabilistic simulation using domain specific metrics automated generation datasets.