Pheromone Accumulation Research Articles

PRRT: An Intelligent Planning Algorithm with Memory

This paper proposes a practically executable path planning method, namely, Pheromones-RRT(PRRT), for robots with a large joint range in a complex environment. To inter-activate with the real world, the point cloud is utilized as the scene information, while for sampling, the pheromones approach is designed to describe the pheromone content carried by each sampling point. During the sampling process, random sampling nodes are performed with a probability of ε, or those nodes with the highest pheromone content in the current sampling tree are selected with a probability of 1-ε and sampled in their neighborhood. To avoid the local minimum problem, the concept of pheromone volatile factor (PVF) is proposed, while in the expansion, double trees are also generated by PRRT in both cartesian and configuration spaces to improve the speed of the algorithm. The pheromone accumulation enables PRRT to certain learning abilities, reducing the randomness of the sampling process. Simulation results show that the proposed method can effectively plan an optimal obstacle avoidance path with satisfactory performances as compared with the RRT-Connect.

Enhanced Hybrid Ant Colony Optimization for Machining Line Balancing Problem with Compound and Complex Constraints

Targeted at the machining production line balancing problem, based on the precedence constraint relation of the present machining task, this article suggests adding practical constraints such as advanced station preparations, post-auxiliary tasks, and tool changing. The study introduced ‘tight’ and ’or’ constraints to bring the problem definition closer to the actual situation. For this problem, a mixed-integer programming model was constructed in this study. The model redefines the machining and auxiliary processing tasks and adds new time constraints to the station. The model considers two optimisation objectives: the number of stations and the machining line balancing rate. In view of the complexity of the problem, heuristic task set filtering mechanisms were designed and added to the ant colony optimisation, to satisfy the above compound and complex constraints. The processing task chain was constructed using the rules of ant colony pheromone accumulation and a random search mechanism. The study designed a Gantt chart generation module to improve the usability and visibility of the program. Ultimately, through an actual case study of a complex box part including 73 processing elements and realising the design and planning of machining production lines that meet complex constraints by substituting algorithms, the balance rates of several groups of optimisation schemes were higher than 90%, which showed that the algorithm is effective and has a good economy and practicability.

A Hybrid BSO-ACO for Dynamic Vehicle Routing Problem on Real-World Road Networks

The Dynamic Vehicle Routing Problem With Time Windows (DVRPTW) is an NP-hard problem, which has attracted a lot of attention in the past decades due to its many practical applications in logistics. In order to better describe the actual logistics distribution scenario, this paper studies the DVRPTW based on real road networks and proposes the hybrid BSO-ACO algorithm, which is a combination of Brain Storm Optimization (BSO), Ant Colony Optimization (ACO) and Neighborhood Search (2-opt, relocate, exchange). The algorithm 1) uses ACO to generate new individuals from the same cluster formed by BSO, and increases exploitation by ACO’s pheromone accumulation, 2) harnesses the 2-opt, relocate, and exchange to increase exploration to avoid the algorithm from falling into local optima. We construct a test set by extracting the real road networks in Panyu District, Guangzhou, China and compare the hybrid BSO-ACO algorithm with other algorithms on this test set. The computation experiments show the effectiveness and efficiency of the hybrid BSO-ACO algorithm.

Solution to Solid Wood Board Cutting Stock Problem

In the production process for wooden furniture, the raw material costs account for more than 50% of furniture costs, and the utilization rate of raw materials depends mainly on the layout scheme. Therefore, a reasonable layout is an important measure to reduce furniture costs. This paper investigates the solid wood board cutting stock problem (CSP) and establishes an optimization model, with the goal of the highest possible utilization rate for original boards. An ant colony-immune genetic algorithm (AC-IGA) is designed to solve this model. The solutions of the ant colony algorithm are used as the initial population of the immune genetic algorithm, and the optimal solution is obtained using the immune genetic algorithm after multiple iterations are transformed into the accumulation of global pheromones, which improves the search ability and ensures the solution quality. The layout process of the solid wood board is abstracted into the construction process of the solution. At the same time, in order to prevent premature convergence, several improved methods, such as a global pheromone hybrid update and adaptive crossover probability, are proposed. Comparative experiments are designed to verify the feasibility and effectiveness of the AC-IGA, and the experimental results show that the AC-IGA has better solution precision and global search ability compared with the ant colony algorithm (ACA), genetic algorithm (GA), grey wolf optimizer (GWO), and polar bear optimization (PBO). The utilization rate increased by more than 2.308%, which provides effective theoretical and methodological support for furniture enterprises to improve economic benefits.

Inversion of pheromone preference optimizes foraging in C. elegans.

Foraging animals have to locate food sources that are usually patchily distributed and subject to competition. Deciding when to leave a food patch is challenging and requires the animal to integrate information about food availability with cues signaling the presence of other individuals (e.g., pheromones). To study how social information transmitted via pheromones can aid foraging decisions, we investigated the behavioral responses of the model animal Caenorhabditis elegans to food depletion and pheromone accumulation in food patches. We experimentally show that animals consuming a food patch leave it at different times and that the leaving time affects the animal preference for its pheromones. In particular, worms leaving early are attracted to their pheromones, while worms leaving later are repelled by them. We further demonstrate that the inversion from attraction to repulsion depends on associative learning and, by implementing a simple model, we highlight that it is an adaptive solution to optimize food intake during foraging.

Ant Colony Optimization Using Common Social Information and Self-Memory

Ant colony optimization (ACO), which is one of the metaheuristics imitating real ant foraging behavior, is an effective method to find a solution for the traveling salesman problem (TSP). The rank-based ant system (ASrank) has been proposed as a developed version of the fundamental model AS of ACO. In the ASrank, since only ant agents that have found one of some excellent solutions are let to regulate the pheromone, the pheromone concentrates on a specific route. As a result, although the ASrank can find a relatively good solution in a short time, it has the disadvantage of being prone falling into a local solution because the pheromone concentrates on a specific route. This problem seems to come from the loss of diversity in route selection according to the rapid accumulation of pheromones to the specific routes. Some ACO models, not just the ASrank, also suffer from this problem of loss of diversity in route selection. It can be considered that the diversity of solutions as well as the selection of solutions is an important factor in the solution system by swarm intelligence such as ACO. In this paper, to solve this problem, we introduce the ant system using individual memories (ASIM) aiming to improve the ability to solve TSP while maintaining the diversity of the behavior of each ant. We apply the existing ACO algorithms and ASIM to some TSP benchmarks and compare the ability to solve TSP.

Optimization of one-dimensional wire cutting with variable length based on genetic ant colony algorithm

This paper presents an algorithm of one-dimensional wire cutting based on genetic algorithm and ant colony algorithm. Firstly, the dominant solution is screened out by genetic algorithm and transformed into the initial accumulation of pheromone in ant colony algorithm, and then the ant colony algorithm is used to adjust the dominant solution of genetic algorithm to obtain the approximate optimal solution. The experimental results show that the convergence rate of the fusion algorithm is faster than that of the ant colony algorithm, and the utilization rate of raw materials is higher than that of genetic algorithm. In addition, the optimal parameters are obtained by adjusting the experimental parameters of the fusion algorithm.

Trails of ants converge or diverge through lens-shaped impediments, resembling principles of optics

Analogies across disciplines often indicate the existence of universal principles such as optimization, while the underlying proximate mechanisms may differ. It was reported recently that trails of ants refract at the border of substrates, on which walking speeds differ. This phenomenon is analogous to the travel-time-minimizing routes of light refracting at the borders between different media. Here, we further demonstrate that ant tracks converge or diverge across lens-shaped impediments similar to light rays through concave or convex optical lenses. The results suggest that the optical principle of travel time reduction may apply to ants. We propose a simple mathematical model that assumes nonlinear positive feedback in pheromone accumulation. It provides a possible explanation of the observed similarity between ant behavior and optics, and it is the first quantitative theoretical demonstration that pheromone-based proximate mechanisms of trail formation may produce this similarity. However, the future detailed empirical observations of ant behavior on impediment edges during the process of pheromone trail formation are needed in order to evaluate alternative explanations for this similarity.

A temporal comparison of sex-aggregation pheromone gland content and dynamics of release in three members of theLutzomyia longipalpis(Diptera: Psychodidae) species complex.

BackgroundLutzomyia longipalpis is the South American vector of Leishmania infantum, the etiologic agent of visceral leishmaniasis (VL). Male L. longipalpis produce a sex-aggregation pheromone that is critical in mating, yet very little is known about its accumulation over time or factors involved in release. This laboratory study aimed to compare accumulation of pheromone over time and determine factors that might influence release in three members of the L. longipalpis species complex.Methodology/Principal findingsWe investigated male sex-aggregation pheromone gland content at different ages and the release rate of pheromone in the presence or absence of females under different light conditions by gas chromatography-mass spectrometry (GC-MS). Pheromone gland content was determined by extraction of whole males and pheromone release rate was determined by collection of headspace volatiles. Pheromone gland content appeared age-related and pheromone began to accumulate between 6 to 12 h post eclosion and gradually increased until males were 7–9 days old. The greatest amount was detected in 9-day old Campo Grande males ((S)-9-methylgermacrene-B; X ± SE: 203.5 ± 57.4 ng/male) followed by Sobral 2S males (diterpene; 199.9 ± 34.3) and Jacobina males ((1S,3S,7R)-3-methyl-α-himachalene; 128.8 ± 30.3) at 7 days old. Pheromone release was not continuous over time. During a 4-hour period, the greatest quantities of pheromone were released during the first hour, when wing beating activity was most intense. It was then substantially diminished for the remainder of the time. During a 24 h period, 4–5 day old male sand flies released approximately 63 ± 11% of the pheromone content of their glands, depending on the chemotype. The presence of females significantly increased pheromone release rate. The light regime under which the sand flies were held had little influence on pheromone release except on Sobral 2S chemotype.Conclusions/SignificanceAccumulation of pheromone appears to occur at different rates in the different chemotypes examined and results in differing amounts being present in glands over time. Release of accumulated pheromone is not passive, but depends on biotic (presence of females) and abiotic (light) circumstances. There are marked differences in content and release between the members of the complex suggesting important behavioural, biosynthetic and ecological differences between them.

Mathematical model for path selection by ants between nest and food source

Several models have been proposed to describe the behavior of ants when moving from nest to food sources. Most of these studies where based on numerical simulations with no mathematical justification. In this paper, we propose a mechanism for the formation of paths of minimal length between two points by a collection of individuals undergoing reinforced random walks taking into account not only the lengths of the paths but also the angles (connected to the preference of ants to move along straight lines). Our model involves reinforcement (pheromone accumulation), persistence (tendency to preferably follow straight directions in absence of any external effect) and takes into account the bifurcation angles of each edge (represented by a probability of willingness of choosing the path with the smallest angle). We describe analytically the results for 2 ants and different path lengths and numerical simulations for several ants.

Application of Ant Colony Algorithm

This paper mainly considers the application of the ant colony in our life. The principle of ant colony optimization, improves the performance of ant colony algorithm, and the global searching ability of the algorithm. We introduce a new adaptive factor in order to avoid falling into local optimal solution. With the increase the number of interations, this factor will benefit the ant search the edge with lower pheromone concentration and avoid the excessive accumulation of pheromone.

Immunocastration with Improvac™ reduces aggressive and sexual behaviours in male pigs

Surgical castration of male pigs is a common practice to reduce the risk of boar taint, an accumulation of pheromones in the muscles of pigs giving an undesirable odour to the pork of entire boars. Castration is not widely practiced in the UK for welfare reasons and indeed, assurance schemes will not allow castrated animals into their markets. Immunocastration maintains entire male pigs in a pre-pubescent state and as such prevents boar taint in the meat. The aim of this study was to investigate the effect of early vaccination with a gonadotrophin releasing factor (GnRF) vaccine Improvac™ (Pfizer Ltd) on aggressive and sexual behaviour of group housed male pigs. Pigs were housed in 8 groups each containing 9–10 pigs per group. Male pigs were assigned to two groups: a control group administered 2 doses of a placebo (n=38) and a vaccinated group administered 2 doses of Improvac™ (n=38). Behavioural observations began one week after the second dose when the pigs were 16 weeks old. Pigs were video recorded for 30min once a week for 10 weeks.Video recordings were reviewed and the frequency of behaviours associated with sex and aggression were recorded on a pen basis. The activity of pigs was also recorded every 5min during the 30min observation period to determine any differences between vaccinated and control groups. A generalised linear mixed model was used for data analysis. The results of the model showed a significant difference between vaccinated and control groups for knocking (P<0.05), fighting (P<0.05) and mounting (P<0.01) behaviours. Vaccination had no significant effect on the activity of pigs during the recording period. In conclusion early immunocastration of pigs significantly reduces the occurrence of unwanted aggressive and sexual behaviours compared with unvaccinated control male pigs.

The Iron-Dependent Regulator Fur Controls Pheromone Signaling Systems and Luminescence in the Squid Symbiont Vibrio fischeri ES114

Bacteria often use pheromones to coordinate group behaviors in specific environments. While high cell density is required for pheromones to achieve stimulatory levels, environmental cues can also influence pheromone accumulation and signaling. For the squid symbiont Vibrio fischeri ES114, bioluminescence requires pheromone-mediated regulation, and this signaling is induced in the host to a greater extent than in culture, even at an equivalent cell density. Our goal is to better understand this environment-specific control over pheromone signaling and bioluminescence. Previous work with V. fischeri MJ1 showed that iron limitation induces luminescence, and we recently found that ES114 encounters a low-iron environment in its host. Here we show that ES114 induces luminescence at lower cell density and achieves brighter luminescence in low-iron media. This iron-dependent effect on luminescence required ferric uptake regulator (Fur), which we propose influences two pheromone signaling master regulators, LitR and LuxR. Genetic and bioinformatic analyses suggested that under low-iron conditions, Fur-mediated repression of litR is relieved, enabling more LitR to perform its established role as an activator of luxR. Interestingly, Fur may similarly control the LitR homolog SmcR of Vibrio vulnificus. These results reveal an intriguing regulatory link between low-iron conditions, which are often encountered in host tissues, and pheromone-dependent master regulators.

An Improved Ant Colony Optimization Applied in Robot Path Planning Problem

an improved Ant colony optimization algorithm (PM-ACO for short) is proposed to solve the robot path planning problem. In PM-ACO, ants deposit pheromone on the nodes but not on the arcs, resulting in that the trails of pheromone become the form of marks, which consist of a series of pheromone points. After ant colony’s tours, the iteration-best strategy is combined with an r-best nodes rule to update the nodes’ pheromone. The stability of PM-ACO is analyzed and some advancement to the algorithm is proposed to improve the performance. Because the pheromone on several arcs is integrated into the pheromone on one node, a rapid pheromone accumulation occurs easily. It is the major causes to the instability. An r-best nodes rule is presented for regulating the pheromone distribution and an adaptive mechanism is designed to further balance the pheromone arrangement. In addition, to shorten the time wasted in constructing the first complete solution and get a better solution, an azimuth guiding rule and a one step optimization rule are used in local optimization. By establishing a grid model of the robot’s navigation area, PM-ACO is applied in solving the robot path planning. Experimental results show that an optimal solution of the path planning problem can be achieved effectively, and the algorithm is practical.

Ant Colony Optimization with Re-Initialization

This contribution introduces an Ant Colony Optimization (ACO) algorithm with re-initialization mechanism. The whole search process is broken by re-initialization into shorter semi-independent steps called “macro cycles”. The length of macro cycle depends on pheromone accumulation and can be adjusted by a user parameter. It is shown that re-initialization mechanism prevents ACO algorithm from pheromone saturation and consecutive stagnation. This approach avoids overhead caused by algorithm run with excessive pheromone values where further exploration is hardly possible. The solution offers lower CPU cost of the search process and enables automation of heuristic search especially in changing environments like dynamic networks. The efficiency of proposed method is demonstrated on a path minimization problem on 50 node graph.

Effects of Flour Conditioning on Cannibalism of &lt;I&gt;T. castaneum&lt;/I&gt; Eggs and Pupae

Cannibalism is a very important factor regulating population dynamics of the red flour beetle. After several days of feeding, the flour becomes conditioned by the beetles, which can affect rates of cannibalism. Flour conditioning is caused by an accumulation of feces, pheromones, and ethylquinone, which is a repellent produced by the beetles. We determined the effect of five different levels of flour conditioning on cannibalism of red flour beetle eggs and pupae by adult and larval stages. Larvae had the highest rates of egg cannibalism (12 eggs eaten over the 4-d period) followed by female adults (seven eggs consumed). Adult males had the lowest rates of cannibalism with only two eggs consumed. Cannibalism of eggs by females was correlated negatively with the level of flour conditioning. There was no effect of flour conditioning on egg or pupal cannibalism by larvae or adult males. Cannibalism by adult females may decrease as the level of flour conditioning increases because females may spend less time tunneling in highly conditioned flour and more time trying to disperse to other areas that are better for oviposition.

Improved Ant Colony Algorithm Base on Slab Cluster for Roll Planning

Focusing on the disadvantages of recent researches for roll planning that seldom consider the warm-up part and solution efficiency is low, in this paper, a parallel planning model and an improved ant colony algorithm were proposed to solve the problem. Firstly, the model considering constraints of both warm-up part and staple one was designed; Secondly, the improved ant colony algorithm was proposed where the slab cluster was used to decrease the searching scope and the local optimization to improve the efficiency of pheromone accumulation. Finally, with production data from hot strip mill, we proof the method can get the best results by comparing with other two ant colony algorithms.

A new and efficient variable selection algorithm based on ant colony optimization. Applications to near infrared spectroscopy/partial least-squares analysis

A new variable selection algorithm is described, based on ant colony optimization (ACO). The algorithm aim is to choose, from a large number of available spectral wavelengths, those relevant to the estimation of analyte concentrations or sample properties when spectroscopic analysis is combined with multivariate calibration techniques such as partial least-squares (PLS) regression. The new algorithm employs the concept of cooperative pheromone accumulation, which is typical of ACO selection methods, and optimizes PLS models using a pre-defined number of variables, employing a Monte Carlo approach to discard irrelevant sensors. The performance has been tested on a simulated system, where it shows a significant superiority over other commonly employed selection methods, such as genetic algorithms. Several near infrared spectroscopic experimental data sets have been subjected to the present ACO algorithm, with PLS leading to improved analytical figures of merit upon wavelength selection. The method could be helpful in other chemometric activities such as classification or quantitative structure-activity relationship (QSAR) problems.

Anatomical site of pheromone accumulation and temporal pattern of pheromone emission in the ambrosia beetle Megaplatypus mutatus

Megaplatypus mutatus (Chapuis) is a native South American ambrosia beetle that attacks live hardwood trees (e.g. Populus spp.), causing important economic losses to commercial plantations. Male beetles release the main components of the sex pheromone, namely (+)‐6‐methyl‐5‐hepten‐2‐ol [(+)‐sulcatol, or retusol] and 6‐methyl‐5‐hepten‐2‐one (sulcatone), when colonizing suitable hosts. The hindgut is shown to be the anatomical site of pheromone accumulation within males, the enantiomeric composition of sulcatol in this tissue is 99%‐(+) and sulcatol is first detectable in this tissue on days 1–2 after gallery initiation. Peak accumulation of sulcatol occurs on days 5–12 after gallery initiation. Trace quantities of sulcatone are also observed during the same period. Both pheromone components are present in male emissions from three host species (Populus×canadensis, Populus alba and Casuarina stricta) between days 2 and 12 after gallery initiation, although sulcatone is always present in low concentrations. The temporal patterns of sulcatol and sulcatone accumulation or storage in male M. mutatus correspond to the temporal patterns of emission.

Characterization of comQ and comX, two genes required for production of ComX pheromone in Bacillus subtilis.

Many microbes use secreted peptide-signaling molecules to stimulate changes in gene expression in response to high population density, a process called quorum sensing. ComX pheromone is a modified 10-amino-acid peptide used by Bacillus subtilis to modulate changes in gene expression in response to crowding. comQ and comX are required for production of ComX pheromone. We found that accumulation of ComX pheromone in culture supernatant paralleled cell growth, indicating that there was no autoinduction of production of ComX pheromone. We overexpressed comQ and comX separately and together and found that overexpression of comX alone was sufficient to cause an increase in production of ComX pheromone and early induction of a quorum-responsive promoter. These results indicate that the extracellular concentration of ComX pheromone plays a major role in determining the timing of the quorum response and that expression of comX is limiting for production of ComX pheromone. We made alanine substitutions in the residues that comprise the peptide backbone of ComX pheromone. Analysis of these mutants highlighted the importance of the modification for ComX pheromone function and identified three residues (T50, G54, and D55) that are unlikely to interact with proteins involved in production of or response to ComX pheromone. We have also identified and mutated a putative isoprenoid binding domain of ComQ. Mutations in this domain eliminated production of ComX pheromone, consistent with the hypothesis that ComQ is involved in modifying ComX pheromone and that the modification is likely to be an isoprenoid.