Pub Date : 2024-01-01Epub Date: 2022-02-22DOI: 10.1007/s11047-022-09880-8
Irina Kostitsyna, Cai Wood, Damien Woods
Molecular robotics is challenging, so it seems best to keep it simple. We consider an abstract molecular robotics model based on simple folding instructions that execute asynchronously. Turning Machines are a simple 1D to 2D folding model, also easily generalisable to 2D to 3D folding. A Turning Machine starts out as a line of connected monomers in the discrete plane, each with an associated turning number. A monomer turns relative to its neighbours, executing a unit-distance translation that drags other monomers along with it, and through collective motion the initial set of monomers eventually folds into a programmed shape. We provide a suite of tools for reasoning about Turning Machines by fully characterising their ability to execute line rotations: executing an almost-full line rotation of radians is possible, yet a full rotation is impossible. Furthermore, line rotations up to are executed efficiently, in expected time in our continuous time Markov chain time model. We then show that such line-rotations represent a fundamental primitive in the model, by using them to efficiently and asynchronously fold shapes. In particular, arbitrarily large zig-zag-rastered squares and zig-zag paths are foldable, as are y-monotone shapes albeit with error (bounded by perimeter length). Finally, we give shapes that despite having paths that traverse all their points, are in fact impossible to fold, as well as techniques for folding certain classes of (scaled) shapes without error. Our approach relies on careful geometric-based analyses of the feats possible and impossible by a very simple robotic system, and pushes conceptional hardness towards mathematical analysis and away from molecular implementation.
分子机器人技术具有挑战性，因此最好保持简单。我们考虑基于异步执行的简单折叠指令的抽象分子机器人模型。旋转机器是一种简单的一维到二维折叠模型，也很容易推广到二维到三维折叠。旋转机器一开始是离散平面上一排相连的单体，每个单体都有一个相关的旋转编号。一个单体相对于其相邻单体转动，执行单位距离平移，拖动其他单体一起转动，通过集体运动，初始单体集最终折叠成编程形状。我们提供了一套用于推理的工具，充分描述了旋转机械执行线性旋转的能力：执行 5 π / 3 弧度的几乎完全线性旋转是可能的，但完全 2 π 旋转是不可能的。此外，在我们的连续时间马尔可夫链时间模型中，最多 5 π / 3 的直线旋转可以在 O ( log n ) 的预期时间内高效执行。然后，我们通过使用这种线旋转来高效、异步地折叠形状，证明这种线旋转代表了模型中的基本原理。特别是，任意大的之字形光栅正方形和之字形路径都是可折叠的，Y-单调形状也是可折叠的，尽管会有误差（以周长为界）。最后，我们给出了一些图形，尽管它们的路径遍历了所有点，但实际上是无法折叠的，我们还给出了无误差折叠某些类别（缩放）图形的技术。我们的方法依赖于对一个非常简单的机器人系统可能完成和不可能完成的任务进行仔细的几何分析，并将概念上的困难推向数学分析，而不是分子实现。
{"title":"Turning machines: a simple algorithmic model for molecular robotics.","authors":"Irina Kostitsyna, Cai Wood, Damien Woods","doi":"10.1007/s11047-022-09880-8","DOIUrl":"10.1007/s11047-022-09880-8","url":null,"abstract":"<p><p>Molecular robotics is challenging, so it seems best to keep it simple. We consider an abstract molecular robotics model based on simple folding instructions that execute asynchronously. Turning Machines are a simple 1D to 2D folding model, also easily generalisable to 2D to 3D folding. A Turning Machine starts out as a line of connected monomers in the discrete plane, each with an associated turning number. A monomer turns relative to its neighbours, executing a unit-distance translation that drags other monomers along with it, and through collective motion the initial set of monomers eventually folds into a programmed shape. We provide a suite of tools for reasoning about Turning Machines by fully characterising their ability to execute line rotations: executing an almost-full line rotation of <math><mrow><mn>5</mn> <mi>π</mi> <mo>/</mo> <mn>3</mn></mrow> </math> radians is possible, yet a full <math><mrow><mn>2</mn> <mi>π</mi></mrow> </math> rotation is impossible. Furthermore, line rotations up to <math><mrow><mn>5</mn> <mi>π</mi> <mo>/</mo> <mn>3</mn></mrow> </math> are executed efficiently, in <math><mrow><mi>O</mi> <mo>(</mo> <mo>log</mo> <mi>n</mi> <mo>)</mo></mrow> </math> expected time in our continuous time Markov chain time model. We then show that such line-rotations represent a fundamental primitive in the model, by using them to efficiently and asynchronously fold shapes. In particular, arbitrarily large zig-zag-rastered squares and zig-zag paths are foldable, as are <i>y</i>-monotone shapes albeit with error (bounded by perimeter length). Finally, we give shapes that despite having paths that traverse all their points, are in fact impossible to fold, as well as techniques for folding certain classes of (scaled) shapes without error. Our approach relies on careful geometric-based analyses of the feats possible and impossible by a very simple robotic system, and pushes conceptional hardness towards mathematical analysis and away from molecular implementation.</p>","PeriodicalId":49783,"journal":{"name":"Natural Computing","volume":"23 2","pages":"407-430"},"PeriodicalIF":1.7,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11297016/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141890710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-25DOI: 10.1007/s11047-023-09968-9
Francisco J. Gil-Gala, Marko Durasević, María R. Sierra, Ramiro Varela
Abstract The Travelling Salesman Problem (TSP) is a well-known optimisation problem that has been widely studied over the last century. As a result, a variety of exact and approximate algorithms have been proposed in the literature. When it comes to solving large instances in real-time, greedy algorithms guided by priority rules represent the most common approach, being the nearest neighbour (NN) heuristic one of the most popular rules. NN is quite general but it is too simple and so it may not be the best choice in some cases. Alternatively, we may design more sophisticated heuristics considering the particular features of families of instances. To do that, we have to consider problem attributes other than the proximity of the next city to build priority rules. However, this process may not be easy for humans and so it is often addressed by some learning procedure. In this regard, hyper-heuristics as Genetic Programming (GP) stands as one of the most popular approaches. Furthermore, a single heuristic, even being good in average, may not be good for a number of instances of a given set. For this reason, the use of ensembles of heuristics is often a good alternative, which raises the problem of building ensembles from a given set of heuristic rules. In this paper, we study the application of two kinds of ensembles to the TSP. Given a set of TSP instances having similar characteristics, we firstly exploit a GP to build a set of heuristics involving a number of problem attributes, and then we build ensembles combining these heuristics by means of a Genetic Algorithm (GA). The experimental study provided valuable insights into the construction and utilisation of single rules and ensembles. It clearly demonstrated that the performance of ensembles justifies the time invested when compared to using individual heuristics.
{"title":"Evolving ensembles of heuristics for the travelling salesman problem","authors":"Francisco J. Gil-Gala, Marko Durasević, María R. Sierra, Ramiro Varela","doi":"10.1007/s11047-023-09968-9","DOIUrl":"https://doi.org/10.1007/s11047-023-09968-9","url":null,"abstract":"Abstract The Travelling Salesman Problem (TSP) is a well-known optimisation problem that has been widely studied over the last century. As a result, a variety of exact and approximate algorithms have been proposed in the literature. When it comes to solving large instances in real-time, greedy algorithms guided by priority rules represent the most common approach, being the nearest neighbour (NN) heuristic one of the most popular rules. NN is quite general but it is too simple and so it may not be the best choice in some cases. Alternatively, we may design more sophisticated heuristics considering the particular features of families of instances. To do that, we have to consider problem attributes other than the proximity of the next city to build priority rules. However, this process may not be easy for humans and so it is often addressed by some learning procedure. In this regard, hyper-heuristics as Genetic Programming (GP) stands as one of the most popular approaches. Furthermore, a single heuristic, even being good in average, may not be good for a number of instances of a given set. For this reason, the use of ensembles of heuristics is often a good alternative, which raises the problem of building ensembles from a given set of heuristic rules. In this paper, we study the application of two kinds of ensembles to the TSP. Given a set of TSP instances having similar characteristics, we firstly exploit a GP to build a set of heuristics involving a number of problem attributes, and then we build ensembles combining these heuristics by means of a Genetic Algorithm (GA). The experimental study provided valuable insights into the construction and utilisation of single rules and ensembles. It clearly demonstrated that the performance of ensembles justifies the time invested when compared to using individual heuristics.","PeriodicalId":49783,"journal":{"name":"Natural Computing","volume":"32 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135113957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-18DOI: 10.1007/s11047-023-09967-w
Pablo García Gómez, Camino R. Vela, Inés González-Rodríguez
Abstract Uncertainty pervades real life and supposes a challenge for all industrial processes as it makes it difficult to predict the outcome of otherwise risk-free activities. In particular, time deviation from projected objectives is one of the main sources of economic losses in manufacturing, not only for the delay in production but also for the energy consumed by the equipment during the additional unexpected time they have to work to complete their labour. In this work we deal with uncertainty in the flexible job shop, one of the foremost scheduling problems due to its practical applications. We show the importance of a good model to avoid introducing unwanted imprecision and producing artificially pessimistic solutions. In our model, the total energy is decomposed into the energy required by resources when they are actively processing an operation and the energy consumed by these resources simply for being switched on. We propose a set of metrics and carry out an extensive experimental analysis that compares our proposal with the more straightforward alternative that directly translates the deterministic model. We also define a local search neighbourhood and prove that it can reach an optimal solution starting from any other solution. Results show the superiority of the new model and the good performance of the new neighbourhood.
{"title":"Neighbourhood search for energy minimisation in flexible job shops under fuzziness","authors":"Pablo García Gómez, Camino R. Vela, Inés González-Rodríguez","doi":"10.1007/s11047-023-09967-w","DOIUrl":"https://doi.org/10.1007/s11047-023-09967-w","url":null,"abstract":"Abstract Uncertainty pervades real life and supposes a challenge for all industrial processes as it makes it difficult to predict the outcome of otherwise risk-free activities. In particular, time deviation from projected objectives is one of the main sources of economic losses in manufacturing, not only for the delay in production but also for the energy consumed by the equipment during the additional unexpected time they have to work to complete their labour. In this work we deal with uncertainty in the flexible job shop, one of the foremost scheduling problems due to its practical applications. We show the importance of a good model to avoid introducing unwanted imprecision and producing artificially pessimistic solutions. In our model, the total energy is decomposed into the energy required by resources when they are actively processing an operation and the energy consumed by these resources simply for being switched on. We propose a set of metrics and carry out an extensive experimental analysis that compares our proposal with the more straightforward alternative that directly translates the deterministic model. We also define a local search neighbourhood and prove that it can reach an optimal solution starting from any other solution. Results show the superiority of the new model and the good performance of the new neighbourhood.","PeriodicalId":49783,"journal":{"name":"Natural Computing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135883124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-21DOI: 10.1007/s11047-023-09964-z
Arnav Solanki, Tonglin Chen, Marc Riedel
{"title":"Parallel pairwise operations on data stored in DNA: sorting, XOR, shifting, and searching","authors":"Arnav Solanki, Tonglin Chen, Marc Riedel","doi":"10.1007/s11047-023-09964-z","DOIUrl":"https://doi.org/10.1007/s11047-023-09964-z","url":null,"abstract":"","PeriodicalId":49783,"journal":{"name":"Natural Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136155440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-31DOI: 10.1007/s11047-023-09957-y
S. Bandini, D. Briola, A. Dennunzio, Francesca Gasparini, Marta Giltri, Giuseppe Vizzari
{"title":"Distance-based affective states in cellular automata pedestrian simulation","authors":"S. Bandini, D. Briola, A. Dennunzio, Francesca Gasparini, Marta Giltri, Giuseppe Vizzari","doi":"10.1007/s11047-023-09957-y","DOIUrl":"https://doi.org/10.1007/s11047-023-09957-y","url":null,"abstract":"","PeriodicalId":49783,"journal":{"name":"Natural Computing","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48990308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-25DOI: 10.1007/s11047-023-09962-1
T. Plénet, F. Bagnoli, S. El Yacoubi, C. Raïevsky, L. Lefèvre
{"title":"Synchronization of elementary cellular automata","authors":"T. Plénet, F. Bagnoli, S. El Yacoubi, C. Raïevsky, L. Lefèvre","doi":"10.1007/s11047-023-09962-1","DOIUrl":"https://doi.org/10.1007/s11047-023-09962-1","url":null,"abstract":"","PeriodicalId":49783,"journal":{"name":"Natural Computing","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45064730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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