A multi-objective grouping Harmony Search algorithm for the optimal distribution of 24-hour medical emergency units

Landa-Torres, Itziar; Manjarres, Diana; Salcedo‐Sanz, Sancho; Ser, Javier Del; Gil-López, Sergio

doi:10.1016/j.eswa.2012.10.051

Cited by 45 publications

(13 citation statements)

References 23 publications

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“…We start by delving into the first solver considered in this study, the Harmony Search (HS) optimization algorithm, which was coined by Geem et al in [15] and subsequently applied to several applications and problems springing from diverse disciplines, such as Energy [20], Transport [15,21], Games [22] and Health operations [23], among many others [24]. …”

Section: Considered Algorithmsmentioning

confidence: 99%

Underwater Robot Task Planning Using Multi-Objective Meta-Heuristics

Landa-Torres

Manjarres

Bilbao

et al. 2017

Sensors

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Robotics deployed in the underwater medium are subject to stringent operational conditions that impose a high degree of criticality on the allocation of resources and the schedule of operations in mission planning. In this context the so-called cost of a mission must be considered as an additional criterion when designing optimal task schedules within the mission at hand. Such a cost can be conceived as the impact of the mission on the robotic resources themselves, which range from the consumption of battery to other negative effects such as mechanic erosion. This manuscript focuses on this issue by devising three heuristic solvers aimed at efficiently scheduling tasks in robotic swarms, which collaborate together to accomplish a mission, and by presenting experimental results obtained over realistic scenarios in the underwater environment. The heuristic techniques resort to a Random-Keys encoding strategy to represent the allocation of robots to tasks and the relative execution order of such tasks within the schedule of certain robots. The obtained results reveal interesting differences in terms of Pareto optimality and spread between the algorithms considered in the benchmark, which are insightful for the selection of a proper task scheduler in real underwater campaigns.

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Section: Considered Algorithmsmentioning

confidence: 99%

Underwater Robot Task Planning Using Multi-Objective Meta-Heuristics

Landa-Torres

Manjarres

Bilbao

et al. 2017

Sensors

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“…The Harmony Search (HS) optimization algorithm was first proposed by Geem et al in [40] and has been lately applied to diverse applications and problems that range from multiple disciplines, such as Energy [41], Games [42], vehicle routing [43], [44] and Health operations [45], among others.…”

Section: A Multi-objective Harmony Search Algorithm (Mohs)mentioning

confidence: 99%

Multi-objective heuristics applied to robot task planning for inspection plants

Landa-Torres

Lobo

MURUA

et al. 2017

2017 IEEE Congress on Evolutionary Computation (CEC)

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Robotics are generally subject to stringent operational conditions that impose a high degree of criticality on the allocation of resources and the schedule of operations in mission planning. In this regard the so-called cost of a mission must be considered as an additional criterion when designing optimal task schedules within the mission at hand. Such a cost can be conceived as the impact of the mission on the robotic resources themselves, which range from the consumption of battery to other negative effects such as mechanic erosion. This manuscript focuses on this issue by presenting experimental results obtained over realistic scenarios of two heuristic solvers (MOHS and NSGA-II) aimed at efficiently scheduling tasks in robotic swarms that collaborate together to accomplish a mission. The heuristic techniques resort to a Random-Keys encoding strategy to represent the allocation of robots to tasks whereas the relative execution order of such tasks within the schedule of certain robots is computed based on the Traveling Salesman Problem (TSP). Experimental results in three different deployment scenarios reveal the goodness of the proposed technique based on the Multi-objective Harmony Search algorithm (MOHS) in terms of Hypervolume (HV) and Coverage Rate (CR) performance indicators.

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“…For example, Forge et al [2] propose the allocation of resources by means of a centralized search of a Pareto frontier driven by several utility functions measuring several properties: assistance quality, cost, reduction resource overuse and balanced resource deployment. Landa-Torres et al [3] use another centralized searching solution based on harmonic algorithms driven by distance and cost to solve the assignment of traffic resources. Centralized proposals, as the previous ones, share the fact that all the resources properties (availability, usage status, etc) are currently known by the central agency.…”

Section: Introductionmentioning

confidence: 99%

A Distributed and Automatic Negotiation Protocol for Resource Allocation in the Management of Traffic Accidents

Farron

García

Tomás

et al. 2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

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Several resources must be devoted to deal with the management of a traffic accident. However, these resources are managed by several independent agencies. The current solutions to coordinate the resources of these agencies are being provided manually by using centralized systems, obviating the distributed nature of the problem. This paper presents a new distributed combinatorial auction PAUSE based protocol suitable to be used in these types of situations. The main innovation in this new protocol is that it allows to allocate efficiently resources grouped by types. In addition it can exploit the existing synergy between the resources provided by any single agency. A multiagent system, MAS, has been programmed to evaluate the performance of this protocol in the traffic accidents domain. The assignments of resources proposed by this MAS show that the protocol provides efficient solutions close to the optimal ones.

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A multi-objective grouping Harmony Search algorithm for the optimal distribution of 24-hour medical emergency units

Cited by 45 publications

References 23 publications

Underwater Robot Task Planning Using Multi-Objective Meta-Heuristics

Underwater Robot Task Planning Using Multi-Objective Meta-Heuristics

Multi-objective heuristics applied to robot task planning for inspection plants

A Distributed and Automatic Negotiation Protocol for Resource Allocation in the Management of Traffic Accidents

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