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Juergen Branke
University of Warwick
44Publications
8H-index
679Citations
Publications 45
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Due to its direct relevance to post-disaster operations, meter reading and civil refuse collection, the Uncertain Capacitated Arc Routing Problem (UCARP) is an important optimisation problem. Stoch...
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#1Juergen Branke (Warw.: University of Warwick)H-Index: 8
#2Wen Zhang (Warw.: University of Warwick)H-Index: 2
Simulation optimisation offers great opportunities in the design and optimisation of complex systems. In the presence of multiple objectives, there is usually no single solution that performs best on all objectives. Instead, there are several Pareto-optimal (efficient) solutions with different trade-offs which cannot be improved in any objective without sacrificing performance in another objective. For the case where alternatives are evaluated on multiple stochastic criteria, and the performance...
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#1Mustafa Demirbilek (Warw.: University of Warwick)H-Index: 1
#2Juergen Branke (Warw.: University of Warwick)H-Index: 8
Last.Arne K. Strauss (Warw.: University of Warwick)H-Index: 9
view all 3 authors...
Human resource planning in home healthcare is gaining importance day by day since companies in developed and developing countries face serious nurse and caregiver shortages. In the problem considered in this paper, the decision of patient assignment must be made immediately when the patient request arrives. Once patients have been accepted, they are serviced at the same days, times and by same nurse during their episode of care. The objective is to maximise the number of patient visits for a set...
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#1Mustafa Demirbilek (Warw.: University of Warwick)H-Index: 1
#2Juergen Branke (Warw.: University of Warwick)H-Index: 8
Last.Arne K. Strauss (Warw.: University of Warwick)H-Index: 9
view all 3 authors...
The importance of home healthcare is growing rapidly since populations of developed and even developing countries are getting older and the number of hospitals, retirement homes, and medical staff do not increase at the same rate. We consider the Home Healthcare Nurse Scheduling Problem where patients arrive dynamically over time and acceptance and appointment time decisions have to be made as soon as patients arrive. The objective is to maximise the average number of daily visits for a single n...
5 CitationsSource
#1Jordan MacLachlan (Victoria University of Wellington)H-Index: 1
#2Yi Mei (Victoria University of Wellington)H-Index: 16
Last.Mengjie Zhang (Victoria University of Wellington)H-Index: 35
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This paper uses a Genetic Programming Hyper-Heuristic (GPHH) to evolve routing policies for the Uncertain Capacitated Arc Routing Problem (UCARP). Given a UCARP instance, the GPHH evolves feasible solutions in the form of decision making policies which decide the next task to serve whenever a vehicle completes its current service. Existing GPHH approaches have two drawbacks. First, they tend to generate small routes by routing through the depot and refilling prior to the vehicle being fully load...
3 CitationsSource
Dec 9, 2018 in WSC (Winter Simulation Conference)
#1Matthew Groves (Warw.: University of Warwick)H-Index: 2
#2Michael Pearce (Warw.: University of Warwick)H-Index: 3
Last.Juergen Branke (Warw.: University of Warwick)H-Index: 8
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Parallelizing Bayesian Optimization has recently attracted a lot of attention. The challenge is usually to estimate the effect multiple new samples will have on the posterior distribution of the objective function, and the combinatorial explosion of the possible sample locations. In this paper, we show that at least for multi-task Bayesian Optimization, parallelization is straightforward because the benefit of samples is independent as long as they are sufficiently far apart in the task space. W...
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#1Michael Pearce (Warw.: University of Warwick)H-Index: 3
#2Juergen Branke (Warw.: University of Warwick)H-Index: 8
Abstract This paper considers the problem of simultaneously identifying the optima for a (continuous or discrete) set of correlated tasks, where the performance of a particular input parameter on a particular task can only be estimated from (potentially noisy) samples. This has many applications, for example, identifying a stochastic algorithm’s optimal parameter settings for various tasks described by continuous feature values. We adapt the framework of Bayesian Optimisation to this problem. We...
3 CitationsSource
#1Matthew Groves (Warw.: University of Warwick)H-Index: 2
#2Juergen Branke (Warw.: University of Warwick)H-Index: 8
This paper proposes a novel sequential sampling scheme to allocate samples to individuals in order to maximally inform the selection step in Covariance Matrix Adaptation Evolution Strategies (CMA-ES) for noisy function optimisation. More specifically we adopt the well-known Knowledge Gradient (KG) method to minimise the Kullback-Leibler divergence (relative entropy) between the distribution used for generating the next offspring population based on the μ selected individuals, and the distributio...
2 CitationsSource
#1Rinde R. S. van Lon (Katholieke Universiteit Leuven)H-Index: 5
#2Juergen Branke (Warw.: University of Warwick)H-Index: 8
Last.Tom Holvoet (Katholieke Universiteit Leuven)H-Index: 29
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Dynamic pickup and delivery problems (PDPs) require online algorithms for managing a fleet of vehicles. Generally, vehicles can be managed either centrally or decentrally. A common way to coordinate agents decentrally is to use the contract-net protocol (CNET) that uses auctions to allocate tasks among agents. To participate in an auction, agents require a method that estimates the value of a task. Typically, this method involves an optimization algorithm, e.g. to calculate the cost to insert a ...
7 CitationsSource
#1Danial Yazdani (LJMU: Liverpool John Moores University)H-Index: 9
#2Trung Thanh Nguyen (LJMU: Liverpool John Moores University)H-Index: 15
Last.Jin Wang (LJMU: Liverpool John Moores University)H-Index: 11
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Dynamic optimization problems (DOPs) are problems that change over time and many real-world problems are classified as DOPs. However, most of investigations in this domain are focused on tracking moving optima (TMO) without considering any other objectives which creates a gap between real-world problems and academic research in this area. One of the important optimization objectives in many real-world problems is previous-solution displacement restriction (PSDR) in which successive solutions sho...
2 CitationsSource
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