Route Length Research Articles

A crossover-based multi-objective discrete particle swarm optimization model for solving multi-modal routing problems

Passengers must use a set of modes and vehicles to reach their destination in complicated urban structures. Choosing an optimal route is a complicated optimization problem for these passengers. This study proposes a multi-objective optimization algorithm to solve the routing problem in the urban multi-modal network. The multi-modal network problem considered in this study is a transportation network with subway, Bus Rapid Transit (BRT), taxi, and walking modes. The objective functions determine the optimized route by considering route length, traffic, comfort, and safety. We develop a Crossover-Based Multi-Objective Discrete Particle Swarm Optimization (CBMODPSO) to solve the problem. CBMODPSO has been improved using mutation and crossover operators. Multi-Objective Artificial Bee Colony (MOABC), Multi-Objective Ant Colony Optimization (MOACO), Multi-Objective Biogeography-Based Optimization (MOBBO), Multi-Objective Gray Wolf Optimization (MOGWO), and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) algorithms are used to evaluate and compare the results from the CBMODPSO algorithm. In addition, CBMODPSO results are compared with previous research results. We show the improved algorithm is more repeatable than other algorithms. The CBMODPSO algorithm has a faster convergence rate and is able to get to an optimal solution in a smaller generation number and much less time. The CBMODPSO algorithm is implemented in about one-thirties of the MOBBO duration. Meanwhile, it has a reproducibility of almost twice the MOGWO algorithm.

Target number influences strategy use by rats (Rattus norvegicus) in the traveling salesperson problem.

The traveling salesman problem (TSP) is an optimization problem in which the goal is to find the shortest possible route that passes through each of a set of points in space. The TSP is of interest not only in the fields of mathematics, computer science, and engineering, but also in cognitive and behavioral research to study problem-solving and spatial navigation. Humans are able to complete even complex TSPs with a high degree of efficiency, and distance minimization in TSP analogs has been observed in a variety of nonhuman species as well. Tasks based on the TSP also have the potential for translational research on cognitive and neurological disorders such as Alzheimer's disease. The current experiment was designed to examine the effects of target number on TSP performance in rats. After pretraining, rats were tested once on each of several target configurations, and their travel routes were recorded. We examined the routes for general efficiency, as well as evidence for strategy use including the nearest neighbor (NN) strategy and crossing avoidance. Our results indicate that latency and route length increase in proportion to the number of targets. Rats also showed a strong tendency to avoid path crossing, and to select NN targets, which strengthened with increasing target numbers. Taken together, our results indicate that travel efficiency decreases linearly in relation to the target number rather than the number of possible routes, which grows factorially with a target number. Additionally, spatial memory and route selection strategy are also affected by an increasing number of targets. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Path Planning of a Mobile Delivery Robot Operating in a Multi-Story Building Based on a Predefined Navigation Tree.

Planning the path of a mobile robot that must transport and deliver small packages inside a multi-story building is a problem that requires a combination of spatial and operational information, such as the location of origin and destination points and how to interact with elevators. This paper presents a solution to this problem, which has been formulated under the following assumptions: (1) the map of the building's floors is available; (2) the position of all origin and destination points is known; (3) the mobile robot has sensors to self-localize on the floors; (4) the building is equipped with remotely controlled elevators; and (5) all doors expected in a delivery route will be open. We start by defining a static navigation tree describing the weighted paths in a multi-story building. We then proceed to describe how this navigation tree can be used to plan the route of a mobile robot and estimate the total length of any delivery route using Dijkstra's algorithm. Finally, we show simulated routing results that demonstrate the effectiveness of this proposal when applied to an autonomous delivery robot operating in a multi-story building.

A study on the possibility of a BUS route network with connections based on an analysis of the efficiency of the BUS route network and resistance OF BUS users to transfer

In this study, data envelopment analysis (DEA) was used to evaluate the efficiency of the bus route network in Akita City, Akita Prefecture, Japan. The DEA efficiency indices utilized route length (km) and overlap index (number of lines/km) as input values for the network efficiency, while the number of buses per year was used as the output value for the deployment efficiency. Operating costs (yen) were used as the input value for the revenue efficiency, and Operating costs (yen) and fare revenue (yen) were used as input and output values, respectively, for the revenue efficiency. The results of this study show that the overall network efficiency is low, indicating that complex and radial bus routes are inefficient and can be improved. Next, we surveyed the attitudes of residents of Akita City, regarding the use of bus routes. The results showed that 18.5% of the respondents did not want to transfer between bus trips, whereas 69.7% could tolerate transferring up to once. Furthermore, 2.7% of the respondents were unwilling to wait for the bus, whereas 52.4% were willing to wait within 10 min, while 38.6% were willing to wait between 10 and 20 min.Based on the results of this analysis, which was conducted by a university laboratory, suggestions were made to the local government on how to provide an efficient network. The bus routes in Akita City are operated by private operators but managed by the local government. Thus, efficient bus routes with connections can be constructed through proposals to local governments.Inefficient bus routes were identified using DEA, and a network with transfers was examined for their improvement. When examining such a network, the attitudes of the users toward transfers must be understood; the relationship involves understanding the attitudes of the users toward inefficient bus routes using DEA. This study revealed that a large number of people could tolerate up to one transfer. The transit time is a significant factor in the acceptance.

A co-evolutionary genetic algorithm with knowledge transfer for multi-objective capacitated vehicle routing problems

The capacitated vehicle routing problem (CVRP) aims to find the routes that minimize transportation costs. However, in real-world applications, the equitable workload is essential for the drivers and logistics companies. For assigning an appropriate load for each vehicle, this paper formulates the CVRP with workload balancing as a multi-objective optimization problem (MO-CVRP). The goal is to simultaneously minimize the total length of routes and the variance of loads assigned to each vehicle. Although several multi-objective evolutionary algorithms (MOEAs) have been proposed for the MO-CVRP, they often suffer from slow convergence speeds due to the complexity of the search space, which hinders the identification of clear search directions. To address this issue, the knowledge transfer method is introduced that can leverage search experiences from related problems to expedite the solution process of the current problem. Specifically, a co-evolutionary genetic algorithm with knowledge transfer is proposed, where a simplified version of the traveling salesman problem (TSP) by disregarding the vehicle capacity constraint is utilized to facilitate the quick solution of the original MO-CVRP. To enable information interaction between these two problems, the widely used denoising autoencoder is adopted to construct a transformation relation between solutions from the TSP to the MO-CVRP. Additionally, an adaptive migration strategy is proposed to adaptively select the migration methods and an improved split operator strategy is designed to ensure the feasibility of the solutions. The proposed algorithm is compared with four state-of-the-art MOEAs on MO-CVRP test sets with different scales. Experimental results show that the proposed algorithm exhibits faster convergence speed and achieves solutions with superior convergence.

Design for Optimally Routing and Scheduling a Tow Train for Just-in-Time Material Supply of Mixed-Model Assembly Lines

With the increase in product varieties, the combination of supermarkets and tow trains is being adopted by more automobile manufacturers for part feeding, especially in mixed-flow assembly lines. This paper focuses on the routing, scheduling, and loading problems of a single towed train that transports parts from one supermarket to the workstation buffer in a mixed-flow assembly line and aims to optimize the loading of the tow train, the optimal delivery schedule and route, and the appropriate departure time to minimize shipping and line inventory costs. To enable part feeding in line with the just-in-time (JIT) principle, a new mixed-integer mathematical model from nonlinearity to linearity and a novel artificial immune genetic algorithm-based heuristic are proposed. Both methods can provide reasonable solutions compared by minimizing the route length and inventory level in terms of speed, and the genetic algorithm shows better performance on a large scale.

Reconstruction of the South Ural Stage of the Punitive Campaign of Tamerlane's Troops Against the Golden Horde in 1391

Relevance. The enormous scientific significance of this topic is due to Russia's belonging to the world of Eurasian civilizations, whose role has been belittled against the background of historical events in Europe. Meanwhile, large-scale processes took place in the Southern Urals in the XIV century, about which there is too little information not only in the educational literature, but also in specialized publications. These include the campaign of the Timurid troops against the Golden Horde in 1391 and its culmination – the Battle of Kondurcha. It was these events that laid the prerequisites for the final collapse of the Jochi Ulus, which in turn accelerated the process of liberating Russian lands from the Horde dependence. The key part of this military campaign is directly connected with the Southern Urals, but the main events of this stage of the campaign (first of all, a major vanguard battle in the west of Orenburg region) still remain unexplored.The purpose: to reconstruct the South Ural stage of the punitive campaign of Tamerlane's troops against the Golden Horde in 1391.Objectives: to make a periodization of the campaign; to determine the affiliation of the hydronyms "Samur" and "Iik" to determine the key points of the campaign; to calculate the average possible speed of movement of Tamerlane's army to identify the possible length of the route of his troops; to find out the approximate localization of the vanguard battle of the opposing sides; to calculate the approximate size of Tamerlane's army.Methodology. The work used a set of general scientific and special methods and principles: the principle of objectivity, the analysis of topographic elements of the terrain, historicism, historical-comparative, chronological, historical analogies and other methods.Results. It was established that the main events of the investigated campaign took place on the territory of the modern Orenburg region, and not Bashkortostan, as indicated in a number of studies. A periodization of the campaign has been compiled, within which two stages of the South Ural stage of this military campaign have been identified. Thanks to the determination of the average speed of movement of troops, it was possible to interpret such hydronyms as "Samur" and "Iik" and establish the approximate location of a major vanguard battle of the opposing armies. With the help of a set of methods, the approximate number of Tamerlane's army was determined.Conclusion. The total length of the South Ural route of the punitive campaign of the Timurid troops in 1391 to the Golden Horde is 700 km, overcome in 21 days. This means that the average speed of movement of troops did not exceed 33 km, which fully fits into the calculations we have given and corresponds to the real capabilities of medieval armies. The presented route is confirmed by archaeological sources, including a unique metal helmet found in the Orenburg region, in the paradise of the Kargalki river. The largest vanguard battle of the considered military campaign took place in the west of Orenburg, on the border of modern Asekeyevsky, Grachevsky, Matveevsky and Krasnogvardeysky districts. The number of troops involved in the campaign is in the range of 50-80 thousand.

Optimizing Municipal Waste Collection: a Case Study of a City in Poland

The main problem of waste management is the increasing amount of municipal waste, and one of the key processes generating high costs is the waste collection process. The aim of the article was to optimize the route of a garbage truck using information technology (IT) software in one of the most populated Polish cities. The article tests the study hypothesis: the use of route optimization software will reduce the route length traveled by the garbage truck of the MZO in Pruszków. The data for the study was made available with the consent of the Municipal Treatment Plant in Pruszków. The received materials included information on, among others, Global Positioning System (GPS) readings of the garbage truck, including route start and end times, route length, average speed, driving time, and time of stops, points selected by the planners to collect waste along the route, information on the amount of waste collected during the implementation of the route, technical data on the moving vehicle and characteristics of the sorting plant were received. The article proposes the optimization of the routes of collection and transportation of municipal waste using the traveling salesman problem (TSP). The minimization of route length was assumed as the optimization criterion. All calculations were made in the Routimo program dedicated to route planning and optimization. As a result of the optimization, the route length was reduced by nearly 32%, and the working time by 9%. Thus, the research hypothesis stated in the article was positively verified.

Analysis of The Ant Number Effects on Ant Colony Optimization for Solving Russia-20-Nodes-SDVRP Instance

SDVRP is a variation of the CVRP that allows different vehicles to visit the same node. ACO performance is influenced by it’s parameter value. The number of ants parameter has a strong influence on ACO Performance, because it influences directly on solution quality and computation time. It is too hard to find the parameter value that can make ACO performance being the best performance. Because of this, what can be done is to test several parameter values, then compare the ACO performance of each parameter value. Russia-20-Nodes-SDVRP Instance is attractive to be solved because it’s number of nodes are not too many, only 20 nodes. Based on that number of nodes, the computation time of this instance is relatively fast and it has a lot of solution candidate. This research focus on the ant number effects on ACO for Solving Russia-20-Nodes-SDVRP Instance. Five ant numbers will be tested, they are 5, 10, 15, 20 and 25 ants, each ant number will be tested 10 times, so there will be 50 tests. These tests show that more ants used, greater possibility of getting a better route, but longer calculation time needed. The decrease in average of length of route is 1,1521% while the increase in average of calculation time is 42.5525%.

Understanding pedestrian route choice behavior in the continuous space: Diversity and equilibrium

Exploring general rules from diverse motion choices in the real world is a pivotal area of study that deepens our understanding of pedestrian behavior. In this research, we conduct pedestrian circle antipode experiments, from which we extract pedestrians' trajectories from repeated trials. We focus on the symmetric features identified from these experiments and employ the K-Medoids trajectory clustering method alongside several behavioral indicators, namely route length, travel time, and comfort level, to distinguish and compare different trajectory route choice patterns. In doing so, we delve into the heterogeneous behaviors exhibited by pedestrians within a single experiment and the stochastic behaviors seen across different experiments for a single pedestrian. Additionally, we establish a linear model to scrutinize the equilibrium relationship among these behavioral indicators, and further deploy the Gaussian process to shed light on the equilibrium characteristics inherent in pedestrian route choice behavior. Our findings suggest that despite the inherent heterogeneity and stochastic nature of individual behaviors, pedestrian route choice overall operates in a dynamic equilibrium state. These insights offer valuable implications for the design of facilities in transport hubs and crowd management strategies in social activities, potentially leading to more effective and organized public spaces.

Multi-Criteria Design of Electric Transit Bus Based on Wireless Charging Infrastructure: A Case Study of Real Road Map in Wakefield

In this paper, a new design strategy is developed for the Wireless Charging Electric Transit Bus (WCETB). The technology is innovative in that the battery in the bus is charged while it is moving over the charging infrastructure. In particular, an improved version of the Whale Optimization Algorithm (IWOA) is adopted for the WCETB system in the road map of Wakefield City, located in the United Kingdom. The main challenge in the WCETB is to select the power transmitter and battery size efficiently from an economical point of view. For this purpose, both factors are considered in the objective function to achieve the benefits of WCETBs from an energy perspective. Two analytical economic design optimization models are developed in this work. The first model is the real- environment model, which considers a WCETB system operating under typical traffic conditions characterized by vehicle interactions and inherent uncertainties. In this scenario, vehicle speeds vary with time, and specific traffic routes may encounter congestion. The second model concentrates on a WCETB system operating in a traffic-free environment with minimal vehicle interactions and uncertainties. The IWOA is implemented for the WCETB to operate in the real environment. Under traffic-free environment conditions, we utilize mathematical procedures and General Algebraic Modeling System (GAMS) software to solve the optimization problem. This approach not only allows us to comprehensively analyze the WCETB system’s behavior but also examine the interactions among different components of the objective function and constraints. Finally, a comprehensive numerical analysis under various conditions, including changes in the number of buses and increases in the length of routes, is conducted.

Impact of wideband wavelength conversion on the performance of optical networks

In this paper, it is proposed and numerically tested a 4 −THz guard-band-less integrated all-optical wavelength converter (iAOWC) with two four-wave mixing (FWM) stages. The nonlinear media used in each stage is a waveguide with a tellurite core that is buried into a SiO2 substrate. The core is shaped as two interleaved spirals connected in their centers by two arcs of a circle to minimize bend loss. The iAOWC can continuously shift a 4 −THz WDM bandwidth from the C- to the L-band and vice versa. In the physical layer simulations, 80×28−GBaud, as DP-QPSK and DP-16QAM, 50-GHz-WDM signals were propagated, respectively, through typical distances found in ultra-long-haul and long-haul transmission systems. For up to four wavelength conversions, the penalties imposed on the signals bit-error-ratios by the iAOWCs were negligible. In the network layer simulations, blocking probabilities were estimated in the CORONET and PANEUR topologies supposing an incremental traffic scenario. Physical layer results were fundamental for the parameters (route lengths, wideband conversion, and spectral shift) considered in the network layer analysis. All network links could carry up to 160 wavelengths that extended from C- to L-band. It is shown that by using an iAOWC with bandwidth of 4-THz instead of 1-THz, both with the same spectral shift capability, to match the blocking probabilities achieved with OEOWCs, this would lead to a reduction of 50% and 40% in the number of required devices for the CORONET and PANEUR topologies, respectively. Finally, this is the first time that it is reported a joint analysis of the physical and network layers regarding the impact of wideband wavelength conversion on the performance of optical networks, specially using an integrated all-optical device and under real-world traffic scenarios.

Crack in Railway Track Detection and Alerting

The Indian Railways is one of the leading public transport systems all over the world with route length over 68,103 KM. However, regardingfacilities, services and safety of people is not yet reached the global standards. Other factors include gaps in between tracks, irregular checks in detecting faults and improper maintenance. The past incidentswhich took place show that the accidents taking place are due to improper maintenance of tracks. But manual checks are still the method used onrailways which are time consuming. The proposed system was designed to overcome the above problems by developing a preprogrammed railway track detection system which is an effective method implemented using Raspberry Pi Pico as a Processor. The IR sensors were used in detecting gaps between railway track and an alert message is sent through Telegram Application along with locality of the fault so the railway department can take necessary steps to avoid accidents and many lives of people.

ГЕНЕТИЧНИЙ АЛГОРИТМ ЯК ЗАСІБ РОЗВ’ЯЗАННЯ ОПТИМІЗАЦІЙНИХ ЗАДАЧ

The article focuses on the peculiarities of using the genetic algorithm (GA) for solving optimization problems. It provides a classification of optimization problems and offers a detailed description of the structural elements of the GA and their role in solving the traveling salesman problem. To assess the impact of GA parameters on its effectiveness, a study on the influence of population size on the length of the traveling salesman's route is conducted. Based on the obtained results, it is shown that population size affects the route length, and the optimal population size for this problem is found to be 150. Using the tournament selection operator, the ordered crossover operator, and the inverse mutation operator, we obtained a salesman's route of 9271.735 km, which, based on the results presented in this paper, is optimal for visiting 29 cities.

Research on Public Air Route Network Planning of Urban Low-Altitude Logistics Unmanned Aerial Vehicles

As urban populations continue to grow and road traffic congestion worsens, traditional ground logistics has become less efficient. This has led to longer logistics times and increased costs. Therefore, unmanned aerial vehicle (UAV) logistics has become increasingly popular. However, free-planned routes cannot meet the safety and efficiency requirements of urban airspace mobility. To address this issue, a public air route network for low-altitude logistics UAVs needs to be established in urban areas. This paper proposes a public route network planning method based on the obstacle-based Voronoi diagram and A* algorithm, as follows: Firstly, construct a city airspace grid model in which the characteristics of the airspace are mapped onto the grid map. Introduce an obstacle clustering algorithm based on DBSCAN to generate representative obstacle points as the Voronoi seed nodes. Utilize the Voronoi diagram to establish the initial route network. Then, conduct an improved path planning by employing the A* algorithm for obstacle avoidance in route edges that pass through obstacles. To ensure the safe operation of drones, set constraints on the route safety interval. This process will generate a low-altitude public air route network for urban areas. After considering the flight costs of logistics UAVs at different altitudes, the height for the route network layout is determined. Finally, the route network evaluation indicators are established. The simulation results demonstrate that compared with the city road network planning method and the central radial network planning method, the total route length is shortened by 7.1% and 9%, respectively, the airspace coverage is increased by 9.8% and 35%, respectively, the average network degree is reduced by 52.6% and 212%, respectively, and the average flight time is reduced by 19.4s and 3.7s, respectively. In addition, by solving the network model using the Dijkstra algorithm, when the energy cost and risk cost weights are 0.6 and 0.4, respectively, and the safety interval is taken as 15 m, the total path cost value of the planned trajectory is minimized.

Properties of bundle valuations in carrier collaboration

Combinatorial auctions are an important part of many frameworks for carrier collaboration in logistics. In the last years, many innovative auction mechanisms have been developed in the economic literature that could potentially be applied in this context and that could significantly simplify the process of determining efficient allocations of requests. These mechanisms rely on certain assumptions about the valuations of bidders. In this paper, we perform computational experiments to analyze to which extent these requirements are fulfilled for valuations derived from a simple logistics problem, the Traveling Salesman Problem. We find that bidders’ valuations typically violate even very elementary requirements, but that these violations affect only a limited number of request bundles. We further analyze whether these violations exhibit a consistent pattern across multiple carriers and check consistency if route lengths are calculated exactly or approximated.

Dual Protection Routing Trees on Graphs

In IP networks, packet forwarding is destination-based and hop-by-hop, and routes are built as needed. Kwong et al. introduced a protection routing in which packet delivery to the destination node can proceed uninterrupted in the event of any single node or link failure. He then showed that “whether there is a protection routing to the destination” is NP-complete. Tapolcai found that two completely independent spanning trees, abbreviated as CISTs, can be used to configure the protection routing. In this paper, we proposed dual protection routing trees, denoted as dual-PRTs to replace CISTs, which are less restrictive than CISTs. Next, we proposed a transformation algorithm that uses dual-PRTs to configure the protection routing. Taking complete graphs Kn, complete bipartite graphs Km,n, hypercubes Qn, and locally twisted cubes LTQn as examples, we provided a recursive method to construct dual-PRTs on them. This article showed that there are no two CISTs on K3,3, Q3, and LTQ3, but there exist dual-PRTs that can be used to configure the protection routing. As shown in the performance evaluation of simulation results, for both Qn and LTQn, we get the average path length of protection routing configured by dual-PRTs is shorter than that by two CISTs.

Using an exact bi-objective decoder in a memetic algorithm for arc-routing (and other decoder-expressible) problems

We address the bi-objective Capacitated Arc Routing Problem (CARP) by considering two levels of solution interpretation: implicit and explicit solutions. An algorithm that translates implicit solutions into explicit solutions is called a decoder. In this work, the decoder takes as input a permutation of the required edges and generates a Pareto frontier of CARP solutions. While bi-objective CARP was our main focus and starting point, we could also use the proposed framework to solve a bi-objective version of the traveling salesman problem by plugging-in a different decoder. Recall that bi-objective CARP asks to service (the demands of) a set of required edges using a fleet of vehicles of limited capacity so as to minimize: (i) the total travelled distance and (ii) the length of the longest route. Any permutation s of the required edges constitutes an implicit CARP solution. The decoder constructs all non-dominated explicit solutions that service the edges in the order indicated by s, i.e., the decoder is an exact algorithm that returns the optimal Pareto frontier subject to the service order s. To achieve competitive CARP results it is also important to reinforce the decoder using a local search operator that acts on explicit routes (and that may change the service order s). For nine instances, the resulting algorithm was even able to find a new total-cost upper bound, improving upon the best solutions reported in the (considerably larger) mono-objective CARP literature. This shows that (some of) the proposed ideas can also be useful in single objective optimization: the second objective can be seen as a guide for the mono-objective search process.

A Novel Method for Extracting and Analyzing the Geometry Properties of the Shortest Pedestrian Paths Focusing on Open Geospatial Data

Unlike car navigation, where almost all vehicles can traverse every route, one route might not be optimal or even suitable for all pedestrians. Route geometry information, including tortuosity, twists and turns along roads, junctions, and road slopes, among others, matters a great deal for specific types of pedestrians, particularly those with limited mobility, such as wheelchair users and older adults. Offering practical routing services to these users requires that pedestrian navigation systems provide further information on route geometry. Therefore, this article proposes a novel method for extracting and analyzing the geometry properties of the shortest pedestrian paths, with a focus on open geospatial data across four aspects: (a) similarity, (b) route curviness, (c) road turns and intersections, and (d) road gradients. Deriving from the Hausdorff distance, a metric called the “dissimilarity ratio” was developed, allowing us to determine whether pairs of routes show any tendencies to be similar to each other. Using the “sinuosity index”, a segment-based technique quantified the route curviness based on the number and degree of the road turns along the route. Moreover, relying upon open elevation data, the road gradients were extracted to identify routes offering smoother motion and better accessibility. Lastly, the road turns and intersections were investigated as pedestrian convenience and safety indicators. A local government area of Greater Sydney in Australia was chosen as the case study. The analysis was implemented on OpenStreetMap (OSM) shortest pedestrian paths against Google Maps as a benchmark for real-world commercial applications. The similarity analysis indicated that over 90% of OSM routes were identical or roughly similar to Google Maps. In addition, while Spearman’s rank correlation showed a direct relationship between route curviness and route length, rS(758) = 0.92, p < 0.001, OSM, on average, witnessed more tortuous routes and, consequently, shorter straight roads between turns. However, OSM routes could be more suitable for pedestrians when the frequency of intersections and road slopes are at the center of attention. Finally, the devised metrics in this study, including the dissimilarity ratio and sinuosity index, showed their practicability in translating raw values into meaningful indicators.

A hybrid iterated local search algorithm for the multi-compartment vehicle routing problem

Multi-compartment vehicle routing problem (MCVRP) is an extension of the classical capacitated vehicle routing problem where products with different characteristics are transported together in one vehicle with multiple compartments. This paper deals with this problem, whose objective is to minimize the total travel distance while satisfying the capacity and maximum route length constraints. We proposed a hybrid iterated local search metaheuristic (HILS) algorithm to solve it. In the framework of iterated local search, the current solution was improved iteratively by five neighborhood operators. For every obtained neighborhood solution after the local search procedure, a large neighborhood search-based perturbation method was executed to explore larger solution space and get a better neighborhood solution to take part in the next iteration. In addition, the worse solutions found by the algorithm were accepted by the nondeterministic simulated annealing-based acceptance rule to keep the diversification of solutions. Computation experiments were conducted on 28 benchmark instances and the experimental results demonstrate that our presented algorithm finds 17 new best solutions, which significantly outperforms the existing state-of-the-art MCVRP methods.