Solving the Steiner tree problem in graphs by chaotic search

Kimura, Takayuki; Ikeguchi, Tohru

doi:10.1587/nolta.11.90

Cited by 4 publications

(6 citation statements)

References 31 publications

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“…The key principles of tabu search are to forbid the search to revisit the recent iterations, aiming to escape from the already encountered local minima. This strategy aims to strike a balance between the algorithm complexity and its performance [18].…”

Section: Related Workmentioning

confidence: 99%

“…In [18], local search techniques have been presented to improve a current solution and chaotic search is employed to escape from an undesirable local minimum. Chaotic search has been demonstrated as an effective metaheuristic for local minima avoidance [32].…”

Section: Related Workmentioning

confidence: 99%

“…It has shown good performance for various NP-hard optimization problems such as travelling salesman [32] and the quadratic assignment problems [34]. The study on the SPG [18] has shown that chaotic search has a higher capability than tabu search in obtaining optimal solutions.…”

Section: Related Workmentioning

confidence: 99%

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Memetic Strategies for Network Design Problems

Amirghasemi

Duong

Hutchison

et al. 2021

Springer Tracts in Nature-Inspired Computing

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Network design problems appear in many areas such as supply chain management, transportation, telecommunication, and Internet of Things (IoT). Many of such problems can be seen as a problem of finding a subset of links and/or nodes, in order to optimize one or more objectives. The nodes can be cities, telecommunication nodes, IoT sensors, warehouse facilities, and the links between those nodes could be roads, network infrastructure, and routes, respectively.In IoT domain, for example, the architecture commonly consists of a number of sensors, devices, cloud servers, and communication protocols to facilitate a wide range of applications such as transportation, smart city, digital living, and e-agriculture [41]. In effect, a typical IoT or telecommunication infrastructure will relay data from remote connected devices to an application. The coverage, robust-

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Memetic Strategies for Network Design Problems

Amirghasemi

Duong

Hutchison

et al. 2021

Springer Tracts in Nature-Inspired Computing

View full text Add to dashboard Cite

show abstract

“…In this context, platelets emerge as a fascinating model for exploring how biological entities solve complex problems swiftly and effectively. Despite their apparent simplicity, the signaling networks of platelets encompass a level of decisional complexity that could potentially mirror the solving of NP-hard problems in computational systems [7].…”

Section: Introductionmentioning

confidence: 99%

Thrombo-inflammation analyzed in a validated seven-layer platelet decision model: cellular decisions are tough problems fast and heuristically solved

Prada,

Balkenhol,

Osmanoglu

et al. 2024

Preprint

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Decisions in biology happen fast and are driven by evolution to optimize survival chances. In platelets, this is achieved by organizing signaling cascades into rapid decision-funnels with modulatory crosstalk. We show that network decision processes underlying cellular decisions are tough to solve (equivalent to classical satisfiability problems, SAT). Hence, heuristics, modular decision-making, and decision funnels are required for efficient decisions.We establish this using a seven-layer platelet decision network that agrees well with all available genetic and functional experimental data. Platelet decision cascades are robust to perturbations: For example, receptors such as TRPM7 modulate platelet activity. However, knockouts of the receptors still leave platelets reactive overall. Dynamic control resolves relaying functions from kinases to cytoskeleton alterations. This allows fast execution of platelet shape change or aggregation. Stress conditions can shift platelet decision funnels towards constant activation of aggregation or immune signaling, causing thrombosis or thrombo-inflammation. Based on the network dynamics, we conclude that platelets pragmatically resolve the complex (non-polynomial (NP)) cellular decision problems by using a similar relaxation to those proposed in mathematics – many different configurations end up in similar states. Metamathematical considerations (no mathematical proof) suggest that NP problems are more complex then P problems.One sentence abstractWe show that cellular decision problems like the platelet signaling cascade may need unexpectedly long to solve but in general, they are efficiently solved using heuristics (“decision funnels”), implying fast decisions but the risk of chronic stress and inflammation.

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“…However, the local search methods cannot find the optimal solution when they are trapped in local minima. To avoid local minima, or to jump out of a local minimum in the search space, several metaheuristics are proposed, such as genetic algorithms [19], simulated annealing [20], neural networks [21][22][23] and the tabu search [24,25]. In this study, we used the tabu search to find better solutions for mBSSRP [24,25].…”

Section: Introductionmentioning

confidence: 99%

Strategy for Exploring Feasible and Infeasible Solution Spaces to Solve a Multiple-Vehicle Bike Sharing System Routing Problem

2021

Self Cite

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In bicycle sharing systems, many vehicles restore bicycles to ports. To construct the shortest tour of these vehicles, in a previous work, we formulated the multiple-vehicle bike sharing system routing problem (mBSSRP) and demonstrated that an optimal solution can be obtained for small-sized instances through a general-purpose mixed-integer linear programming solver. However, for large-sized instances, the optimal solution could not be found in a reasonable time frame. Therefore, to find near-optimal solutions for the mBSSRPs in a short time, in this study, we develop a method with a searching strategy, which explores both the feasible and infeasible solution spaces. To investigate the performance of the proposed method, we solve benchmark problems of mBSSRP. In addition, we compare the proposed method with the method exploring only the feasible solution space, in terms of performance. The results of the numerical experiments demonstrate that the proposed method can reach optimal solutions for almost all small-sized mBSSRP instances and that searching both the feasible and infeasible solution spaces yields good feasible solutions both for small-sized and large-sized instances.

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Solving the Steiner tree problem in graphs by chaotic search

Cited by 4 publications

References 31 publications

Memetic Strategies for Network Design Problems

Memetic Strategies for Network Design Problems

Thrombo-inflammation analyzed in a validated seven-layer platelet decision model: cellular decisions are tough problems fast and heuristically solved

Strategy for Exploring Feasible and Infeasible Solution Spaces to Solve a Multiple-Vehicle Bike Sharing System Routing Problem

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