Behavior Of Whales Research Articles

Cooperative feeding and foraging lateralization by Eden's whales off southern China

AbstractWe investigated surface feeding behaviors of Eden's whales (Balaenoptera edeni edeni) in northern Beibu Gulf, southern China, between April 3, 2018, and April 26, 2021. During 122 days at sea, 1,065 individual feeding events were recorded, and eight feeding behaviors were identified: two nonlunging (tread‐water and/or trap‐feeding, 7.7%, and a novel behavior we call “pirouette feeding,” 15.3%) and six lunging (right lateral lunging, RLL, 10.9%; left lateral lunging, 0.2%; upright lunging, 6.3%, vertical lunging, 18.5%; inverted lunging, 0.3%; cooperative lateral lunging, COL, 40.9%). During COL, 2–8 whales swam clockwise around a fish school and simultaneously performed RLL on surfacing—the first cooperative feeding behavior recorded for a Balaenoptera whale. Five lateralized feeding behaviors (entailing either a left or right rotation on the long‐body axis) accounted for 65.8% of individual feeding events, with a strong right‐side bias (99.7%). Lateralized behavior is prevalent in many vertebrates, including several species of rorquals, and we suggest that the right‐biased foraging lateralization among rorquals specifically allows them to keep their right eye on their prey (i.e., a sensory versus motor lateralization), and that this shared asymmetry among conspecifics may have preadapted Eden's whale for cooperative foraging.

Western gray whale behavioral response to seismic surveys during their foraging season

Gray whales utilizing their foraging grounds off northeastern Sakhalin Island, Russia, have been increasingly exposed to anthropogenic activities related to oil and gas development over the past two decades. In 2015, four seismic vessels, contracted by two operators, conducted surveys near and within the gray whale feeding grounds. Mitigation and monitoring plans were developed prior to the survey and implemented in the field, with real-time data transfers to assist the implementation of measures aimed at minimizing impacts of acoustic exposure. This study examined the behavioral response of gray whales relative to vessel proximities and sounds generated during seismic exploration. Five shore-based teams monitored gray whale behavior from 1 June to 30 September using theodolite tracking and focal follow methodologies. Behavioral data were combined with acoustic and benthic information from studies conducted during the same period. A total of 1270 tracks (mean duration = 0.9 h) and 401 focal follows (1.1 h) were collected with gray whales exposed to sounds ranging from 59 to 172 dB re 1 μPa2 SPL. Mixed models were used to examine 13 movement and 10 respiration response variables relative to “natural,” acoustic, and non-acoustic explanatory variables. Water depth and behavioral state were the largest predictors of gray whale movement and respiration patterns. As vessels approached whales with increasing seismic/vessel sound exposure levels and decreasing distances, several gray whale movement and respiration response variables significantly changed (increasing speed, directionality, surface time, respiration intervals, etc.). Although the mitigation measures employed could have reduced larger/long-term responses and sensitization to the seismic activities, this study illustrates that mitigation measures did not eliminate behavioral responses, at least in the short-term, of feeding gray whales to the activities.

Comparing the social signaling behavior of humpback whales in three group types on the Hawaiian breeding grounds using acoustic tags

Humpback whales (Megaptera novaeangliae) are exceptionally vocal among baleen whale species. While extensive research has been conducted on humpback whale songs, gaps remain in our understanding of other forms of communication, particularly non-song calls. Here, we compare the spectral features and temporal parameters of non-song calls recorded from AcousondeTM tagged humpback whales in three commonly observed group types in the breeding grounds: adult dyads (N = 3), singly escorted mother-calf pairs (N = 4), and competitive groups (N = 4). Recordings were collected off Maui, Hawai’i during the winter breeding seasons of 2019–2021. Individual calls were identified based on visual and aural inspection of spectrograms using Raven Pro 1.6 software, with a total of 842 calls isolated from 47.6 h of acoustic recordings. Competitive groups produced the most calls (N = 358); however, after adjusting for the differences in recording hours and the number of individuals, the call rate (calls/hour/whale) was not significantly different between group compositions. The temporal parameters and frequency measures of calls did not vary significantly across the groups. However, interesting patterns of calling behavior were observed (e.g., competitive groups had the shortest inter-call intervals and the highest frequency calls, and escorted mother-calf pairs had the longest inter-call intervals) and it is possible the lack of statistical significance could be attributed to the small sample size of tag deployments. This study provides new insights into humpback whale vocal communication behavior in the Hawaiian Islands breeding grounds.

A satellite-linked tag for the long-term monitoring of diving behavior in large whales

Despite spending most time underwater, the technology in use to track whales over large geographic ranges via satellite has been largely limited to locational data, with most applications focusing on characterizing their horizontal movements. We describe the development of the RDW tag, a new Argos-based satellite telemetry device that incorporates sensors for monitoring the movements and dive behavior of large whales over several months without requiring recovery. Based on an implantable design, the tag features a saltwater conductivity switch, a tri-axial accelerometer, and an optional pressure transducer, along with onboard software for data processing and detection of behavioral events or activities of interest for transmission. We configured the software to detect dives and create per-dive summaries describing behavioral events associated with feeding activities in rorqual whales. We conducted a validation by proxy of the dive summary and event detection algorithms using field data from a medium-duration archival tag. We also conducted a simulation exercise to examine how the expected data recovery would vary under different dive behavior scenarios and compared those results to empirical values from field deployments of the RDW tag on blue (Balaenoptera musculus) and humpback (Megaptera novaeangliae) whales. The dive summary algorithm accurately reported dive depth and duration, while the accuracy of the lunge-feeding event detection algorithm was dependent on the precision of the accelerometer data that was used, with a predicted accuracy of 0.74 for correctly classifying feeding dives from 1/64-G precision data and 0.95 from 1-mG precision data. Simulated data recovery was lower with sparser transmission schedules, shorter mean dive durations, and lower rates of successfully received transmissions. Empirical data recovery was lower than expected from the simulation, suggesting the effect of additional factors, such as data gaps. By measuring key aspects of the per-dive behavior of large whales over multi-month timescales of movement, the RDW tags provide the ability to monitor previously unobservable behaviors across entire geographic ranges, extending the applications of satellite telemetry devices to new areas of whale physiology, behavior, ecology, and conservation.

Echolocation depths and acoustic foraging behavior of Baird's beaked whales (Berardius bairdii) based on towed hydrophone recordings

Echolocation depths and acoustic foraging behavior of Baird's beaked whales (<i>Berardius bairdii</i>) based on towed hydrophone recordings

OPTIMAL PROTECTION COORDINATION OF RELAYS IN PRESENCE OF DISTRIBUTED GENERATION USING WHALE ALGORITHM

“This paperis proposes a novel nature-inspired meta-heuristic optimization algorithm, called Whale Optimization Algorithm (WOA), which mimics the social behavior of the humpback whales. The algorithm is inspired by the bubble-net hunting strategy”which is good comparing to others. WOA is tested with 29 mathematical optimization problems and structural design problems. Optimization results prove that the WOA algorithm is very competitive compared to the state the of art meta heuristic algorithms as well as conventional methods

Dive Behavior and Activity Patterns of Fin Whales in a Migratory Habitat

Efficient use of the energy budget is of fundamental importance for long-distance migrants, which must cope with seasonal energy demands and environmental conditions. Time-activity budgets can provide information on how animals balance energy use and acquisition over their annual cycle, and on the costs and benefits of different migratory strategies. Baleen whales, such as the fin whale, perform long migrations between feeding and breeding grounds. Although there are now a handful of studies describing the diving and foraging behavior of fin whales, most were carried out at their high-latitude foraging grounds, and very little is known about their behavior in wintering habitats or during migration. We analyzed time-depth recorder data to describe the diving behavior and activity patterns of fin whales in a migratory habitat. Using a hierarchical cluster analysis based on a set of dive variables, we identified six dive types. Four of these dive types (shallow exploratory, shallow active, deep exploratory and deep active) were likely associated to foraging. The other two comprised long non-active dives and dives of variable shape, which may represent resting, traveling or even vocalizing behavior. Shallow exploratory dives were the most frequent dive type (23%) and shallow active were the least frequent (5%). The two deepest dive types, deep active and exploratory, were predominantly carried out during the day, and night dives were significantly shallower than daylight dives, suggesting that fin whales tracked the vertical migration of prey. Whales spent 60% of their dive time engaged in dives associated with feeding and/or prey searching, suggesting they prioritized energy intake over energy conservation. Finally, we found that whales spent more time at or close (&amp;lt;15 m depth) to the surface at night (73%) than during the day (55%), indicating a higher vulnerability to ship strikes during this period. Our study provides novel information on the behavioral patterns and time-activity budgets of fin whales in a migratory habitat. This information is essential for bioenergetic analyses and to predict how fin whales respond to human activities and ongoing environmental changes.

Beluga whale optimization: A novel nature-inspired metaheuristic algorithm

In this paper, a novel swarm-based metaheuristic algorithm inspired from the behaviors of beluga whales, called beluga whale optimization (BWO), is presented to solve optimization problem. Three phases of exploration, exploitation and whale fall are established in BWO, corresponding to the behaviors of pair swim, prey, and whale fall, respectively. The balance factor and probability of whale fall in BWO are self-adaptive which play significant roles to control the ability of exploration and exploitation. Besides, the Levy flight is introduced to enhance the global convergence in the exploitation phase. The effectiveness of the proposed BWO is tested using 30 benchmark functions, with qualitative, quantitative and scalability analysis, and the statistical results are compared with 15 other metaheuristic algorithms. According to the results and discussion, BWO is a competitive algorithm in solving unimodal and multimodal optimization problems, and the overall rank of BWO is the first in the scalability analysis of benchmark functions among compared metaheuristic algorithms through the Friedman ranking test. Finally, four engineering problems demonstrate the merits and potential of BWO in solving complex real-world optimization problems. The source code of BWO is currently available to public: https://ww2.mathworks.cn/matlabcentral/fileexchange/112830-beluga-whale-optimization-bwo/.

Community Impact on a Cryptocurrency: Twitter Comparison Example Between Dogecoin and Litecoin

Context: The third generation of cryptocurrencies gathers cryptocurrencies that are as diverse as the market is big (e.g., Dogecoin or Litecoin). While Dogecoin is seen as a memecoin, the other gathers a very different category of investors. To our knowledge, no study has independently assessed the crypto community’s economical impact on these cryptocurrencies. Furthermore, various methodological possibilities exist to forecast cryptocurrency price—mainly coming from online communities.Method: Our study has retrospectively studied (from 01/01/2015 to 03/11/2021)—using open access data—the association strength (using normalized mutual information) and the linear correlation (using Pearson’s correlation) between Twitter activity and cryptocurrency economical attributes. In addition, we have computed different models (ADF, ARIMA, and Interpretable MultiVvariable Long Short-Term Memory recurrent neural network) that forecast past price values and assessed their precision.Findings and conclusions: While the average Dogecoin transaction value is impacted by tweets, tweets are impacted by Litecoin transactions number and average Litecoin transaction value. Tweet number is impacted by Dogecoin whale behavior, but no significant relationship was found between Litecoin whales and tweets. The forecasting error resulting from our ARIMA (0,0,0) models was 0.08% (with Litecoin) and 0.22% (with Dogecoin). Therefore, those are just the beginning of scientific findings that may lead to building a trading robot based on these results. However, in itself, this study is only for academic discussion, and conclusions need to be drawn by further research. The authors cannot be liable if any financial investment is made based on its conclusions.

Insights into acoustic behavior of false killer whales

The Hawaiian Archipelago is home to three distinct populations of false killer whales (Pseudorca crassidens), including one currently listed as endangered. These delphinids are known to interact with fishing gear, leading to whale mortality or injury. Hence, it is critical to assess the abundance of these populations typically achieved through visual-based sighting surveys. However, these surveys are complicated by a number of biases and uncertainties specific to this species. Passive acoustics could aid in monitoring of their population status, but the knowledge is limited about the patterns in their acoustic repertoire and behavior, which hinders our ability to derive reliable acoustics-based abundance estimates. Here, we discuss insights into the acoustic behaviour of false killer whales in the wild, gained by simultaneous tracking of both narrowband whistles and broadband echolocation clicks from towed hydrophone arrays. The results indicate a diverse acoustic behaviour between different subgroups within the same encounter, where 23.8% of subgroups (N total = 408) only echolocate, 18.9% only whistle, and 57.3% emit both types of vocalizations. Such increased understanding of false killer whale vocal behavior can contribute information from passive acoustic data for management and conservation purposes.

Autumn acoustic behavior of right whales in Southern New England waters

North Atlantic right whales (Eubalaena glacialis) are an endangered species of baleen whale found in high human use areas off the East Coast of the United States. Conservation efforts for this species include the use of passive acoustic monitoring to detect sounds produced by right whales to determine when they are present in areas of interest. Right whale acoustic behavior is known to vary by age, sex, and behavioral state, with differing call types and call rates found across different habitats and seasons. There are currently plans for development of offshore wind energy installations off the East Coast of the United States, including lease areas south of Massachusetts in areas known to be frequented by right whales. These development plans necessitate a better understanding of right whale acoustic behavior in this region to best inform passive acoustic monitoring efforts for right whales. In this study, we analyzed ∼38 h of data from eight suction cup archival acoustic biologging tags attached to North Atlantic right whales in October 2021 in Southern New England waters south of Nantucket. The call types and call rates by behavioral state will be discussed with the primary observed behaviors including foraging and social surface behaviors.

Passive acoustic tracking of the three‐dimensional movements and acoustic behaviour of toothed whales in close proximity to static nets

Abstract Entanglement in net fisheries (static and drift) is the largest known cause of direct anthropogenic mortality to many small cetacean species, including harbour porpoise (Phocoena phocoena), in UK waters. Despite this, little is known about the behaviour of small cetaceans in proximity to nets. We have developed a passive acoustic monitoring (PAM) system for tracking the fine‐scale three‐dimensional (3D) movements of echolocating cetaceans around actively fishing nets by localising their acoustic clicks. The system consists of two compact four‐channel acoustic recorders with sample‐synchronised sensor packages that use 3D motion tracking technology to accurately log orientation, depth, water temperature and ambient light level. Two recorders were used in tandem, with each one attached to and floating above the net floatline. The system can be deployed during normal fishing operations by a trained researcher or experienced fisheries observer. Recordings were analysed in PAMGuard software and the 3D positions of echolocating animals in the vicinity of the system were calculated using an acoustic particle filter‐based localisation method. We present findings from four deployments in UK waters (each 1–2 days in duration) in which 12 distinct harbour porpoise encounters yielded a sufficient number of detected clicks to track their movements around the net. The tracks show a variety of behaviours, including multiple instances of animals actively foraging in close proximity to the fishing net. We show that a relatively inexpensive PAM system, which is practical to deploy from active fishing vessels, is capable of providing highly detailed data on harbour porpoise behaviour around nets. As harbour porpoises are the one of the most difficult species to localise, this methodology is likely to be suitable for elucidating the behaviour of many other toothed whale species in a variety of situations.

Feeding tactics of resident Bryde's whales in New Zealand

AbstractLarge predators typically feed on proportionally sized prey but the world's largest animals, baleen whales, bulk feed on plankton and small fishes. While most baleen whales migrate to feed on polar aggregations of nutritious zooplankton prey, Bryde's whales (Balaenoptera edeni brydei and B. e. edeni) inhabit less productive warm‐temperate waters with variable prey abundance and quality. Off New Zealand, Bryde's whales target both fish and zooplankton, some with lower calorific value. We use multisensor tags (n = 4) and visual observations from drones and boats (n = 52) to reveal that Bryde's whales employ specialized feeding tactics matched to prey type. Zooplankton‐feeding at the surface involved multiple head‐slaps that presumably aggregate zooplankton followed by a side‐lunge. Whales exploiting plankton patches swam in tight circles, performing up to 33 lunges (M = 5.5 ± 6.1) per feeding bout. In contrast, whales targeting fish performed faster vertical lunges. With both prey types, whales concluded lunges with a ~90° roll probably to minimize prey escape at the surface. The diet plasticity and dynamic behaviors of Bryde's whales are key to increasing their foraging efficiency. This may be essential for the whales to meet energetic demands year‐round with a variety of prey in New Zealand waters.

Characterizing the suckling behavior by video and 3D-accelerometry in humpback whale calves on a breeding ground.

Getting maternal milk through nursing is vital for all newborn mammals. Despite its importance, nursing has been poorly documented in humpback whales (Megaptera novaeangliae). Nursing is difficult to observe underwater without disturbing the whales and is usually impossible to observe from a ship. We attempted to observe nursing from the calf’s perspective by placing CATS cam tags on three humpback whale calves in the Sainte Marie channel, Madagascar, Indian Ocean, during the breeding seasons. CATS cam tags are animal-borne multi-sensor tags equipped with a video camera, a hydrophone, and several auxiliary sensors (including a 3-axis accelerometer, a 3-axis magnetometer, and a depth sensor). The use of multi-sensor tags minimized potential disturbance from human presence. A total of 10.52 h of video recordings were collected with the corresponding auxiliary data. Video recordings were manually analyzed and correlated with the auxiliary data, allowing us to extract different kinematic features including the depth rate, speed, Fluke Stroke Rate (FSR), Overall Body Dynamic Acceleration (ODBA), pitch, roll, and roll rate. We found that suckling events lasted 18.8 ± 8.8 s on average (N = 34) and were performed mostly during dives. Suckling events represented 1.7% of the total observation time. During suckling, the calves were visually estimated to be at a 30–45° pitch angle relative to the midline of their mother’s body and were always observed rolling either to the right or to the left. In our auxiliary dataset, we confirmed that suckling behavior was primarily characterized by a high average absolute roll and additionally we also found that it was likely characterized by a high average FSR and a low average speed. Kinematic features were used for supervised machine learning in order to subsequently detect suckling behavior automatically. Our study is a proof of method on which future investigations can build upon. It opens new opportunities for further investigation of suckling behavior in humpback whales and the baleen whale species.

A Modified Whale Optimization Algorithm and Its Application in Seismic Inversion Problem

The whale optimization algorithm (WOA) is a popular swarm intelligence algorithm which simulates the hunting behavior of humpback whales. WOA has the deficiency of easily falling into the local optimal solutions. In order to overcome the weakness of the WOA, a modified variant of WOA called OCDWOA is proposed. There are four main operators introduced into the OCDWOA to enhance the search performance of WOA. The operators include opposition-based learning method, nonlinear parameter design, density peak clustering strategy, and differential evolution. The proposed algorithm is tested on 19 optimization benchmark functions and a seismic inversion problem. OCDWOA is compared with the classical WOA and three typical variants of WOA. The results demonstrate that OCDWOA outperforms the compared algorithms in terms of obtaining the global optimal solution.

The effect of group size on individual behavior of bubble‐net feeding humpback whales in the southern Gulf of Maine

AbstractIn many species, group foraging is a strategy used to increase the efficiency of individuals to find and exploit patchy prey. Humpback whales (Megaptera novaeangliae) are one of the few baleen whale species reported to use coordinated foraging strategies. One of these behaviors, bubble‐net feeding, has been observed in several populations, though the behaviors of individuals within these groups are largely unknown. This study used multisensor kinematic tag data from 26 whales foraging in the Southern Gulf of Maine to analyze individual bubble‐net feeding behaviors. Linear mixed effects models were used to test if there were differences in individual whales' dive behaviors across group size. The results indicate that individuals performed consistent bubble‐net feeding behaviors regardless of the size of their foraging group, except when using one specific foraging behavior, the upward spiral. Overall complexity of foraging dives, based on the three‐dimensional movements of the dive, decreased with increasing group size when group members used upward spirals. This may indicate that in larger groups, participants in coordinated feeding events need to move less and expend less energy to corral prey. This study provides new insights into the effects of group size on individual behavior and group coordination in humpback whales.

Year-Round Dive Characteristics of Male Beluga Whales From the Eastern Beaufort Sea Population Indicate Seasonal Shifts in Foraging Strategies

Dive behavior represents multiple ecological functions for marine mammals, but our understanding of dive characteristics is typically limited by the resolution or longevity of tagging studies. Knowledge on the time-depth structures of dives can provide insight into the behaviors represented by vertical movements; furthering our understanding of the ecological importance of habitats occupied, seasonal shifts in activity, and the energetic consequences of targeting prey at a given depth. Given our incomplete understanding of Eastern Beaufort Sea (EBS) beluga whale behavior over an annual cycle, we aimed to characterize dives made by belugas, with a focus on analyzing shifts in foraging strategies. Objectives were to (i) characterize and classify the range of beluga-specific dive types over an annual cycle, (ii) propose dive functions based on optimal foraging theory, physiology, and association with environmental variables, and (iii) identify whether belugas undergo seasonal shifts in the frequency of dives associated with variable foraging strategies. Satellite-linked time-depth-recorders (TDRs) were attached to 13 male belugas from the EBS population in 2018 and 2019, and depth data were collected in time series at a 75 s sampling interval. Tags collected data for between 13 and 357 days, including three tags which collected data across all months. A total of 90,211 dives were identified and characterized by twelve time and depth metrics and classified into eight dive types using a Gaussian mixed modeling and hierarchical clustering analysis approach. Dive structures identify various seasonal behaviors and indicate year-round foraging. Shallower and more frequent diving during winter in the Bering Sea indicate foraging may be energetically cheaper, but less rewarding than deeper diving during summer in the Beaufort Sea and Arctic Archipelago, which frequently exceeded the aerobic dive limit previously calculated for this population. Structure, frequency and association with environmental variables supports the use of other dives in recovery, transiting, and navigating through sea ice. The current study provides the first comprehensive description of the year-round dive structures of any beluga population, providing baseline information to allow improved characterization and to monitor how this population may respond to environmental change and increasing anthropogenic stressors.

Using sonobuoys and visual surveys to characterize North Atlantic right whale (Eubalaena glacialis) calling behavior in the Gulf of St. Lawrence

The appropriate use and interpretation of passive acoustic data for monitoring the Critically Endangered North Atlantic right whaleEubalaena glacialis(hereafter right whale) rely on knowledge of their calling behavior and how it varies with respect to time, space, demographics, and observed behavior. To assess such relationships in a habitat of increased management importance, sonobuoys (disposable drifting hydrophones) were deployed in the Gulf of St. Lawrence, Canada, to record sounds from aggregating right whales during visual aerial surveys in the summers (June through August) of 2017 (n = 8), 2018 (n = 13), and 2019 (n = 16). Upcalls, gunshots, and various mid-frequency (250-800 Hz) tonal calls were compared to demographics and observed behaviors of concurrently observed right whales using correlation matrices, linear regressions, and generalized linear models. Our results show that (1) call rates increased from June to August for all call types; (2) calling rates were associated negatively with observed foraging behavior and positively with observed socializing behavior; (3) upcalls were occasionally produced at higher rates (&gt;20 calls h-1) when in association with gunshots and tonal calls; (4) acoustic monitoring did not always detect right whale presence at fine timescales (2-6 h), but presence estimates were improved when multiple calls types were considered; and (5) calling rates were too variable to provide reliable density estimates of observed right whales. These results have important implications for the interpretation of passive acoustic monitoring in this habitat and provide evidence that some whale behaviors (e.g. socializing) may be reliably inferred from acoustics alone.

Abundance, distribution and behaviour of humpback whales (

Context Previous research has shown the presence of an endangered humpback whale population breeding off the Pacific coast of Central America. However, little is known about the density, size, social-group structure and spatial habitat use of this subpopulation. Aim The study goal was to characterise a potential breeding subpopulation of humpback whales in the waters off Nicaragua. Five objectives were used to achieve this goal: (1) estimate abundance, (2) determine encounter rates, (3) define group composition, (4) assess distribution, and (5) document habitat-use patterns. Method Boat-based surveys were conducted between November and April at two study sites along the Pacific coast of Nicaragua in the winters of 2004–2008 and 2016–2020. Key result Inter-annual mark–recapture estimates did not yield a reliable estimate of abundance. Encounter rates were lower for the northern study site than for the southern site. Group composition consisted of groups with calves, singers and competitive males. Conclusion These results confirmed that Nicaragua is a breeding area based on known breeding-ground behaviours observed in other areas, and similar environmental characteristics. Implication Distinct habitats were found at the two study sites, suggesting that Central American humpback whales might use different areas within the broader Central American breeding range according to their needs and activity.

Seismic Inversion Problem Using a Multioperator Whale Optimization Algorithm

The whale optimization algorithm (WOA) is a metaheuristic algorithm based on swarm intelligence and it mimics the hunting behavior of whales. It has the imperfection of premature convergence into local optima. In order to overcome this disadvantage, a multioperator WOA (MOWOA) is proposed. Four main strategies are introduced to the MOWOA to heighten the search capacity of WOA. The strategies include nonlinear adaptive parameter design, an exploration mechanism of honey badger, Cauchy factor strategy, and greedy strategy. This paper tests the versatility of MOWOA with three different types of benchmark functions, and a kind of seismic inversion problem are trialed run. From the experimental results, the performance of MOWOA outperforms the compared algorithms in global optimization.