Optimal Transportation Routes Research Articles

The importance of high crop residue demand on biogas plant site selection, scaling and feedstock allocation – A regional scale concept in a Hungarian study area

In regions characterised by intensive agriculture, livestock manure is a commonly used feedstock for biogas production. Due to its expensive transportation, manure sources are often the sole criteria during biogas plant site selection, regarding feedstock supply. Encouraging biogas plant operators to use larger amounts of crop residues in the feedstock is favourable from an energy management viewpoint, but its spatial projection on resource logistics and its significance on biogas plant selection is less investigated. In this study, scenarios were created with different feedstock compositions considering constant manure and varying crop residue ratios. Based on their potential biogas yields and the location of livestock farms, a manure source-oriented site selection and facility scaling was made in a Hungarian study area. The applied GIS-based feedstock allocation and logistic analysis defined the crop acquisition possibilities and optimal transportation routes, assuming multiple resource-competitive biogas plants. The results indicate that feedstock composition can indirectly impact the site selection procedure and supply security if high crop residue demand is considered. Resource acquisition possibilities and economic feasibility are significantly affected by the location and density of the proposed biogas plants and their relative position to the crop supply areas. Due to the geographical heterogeneity of the supply side and the demand points, the transportation costs of crop residues and the digestate exceed those of the manure in all scenarios, which draws attention to the importance of spatial availability of crop residues during biogas plant site selection and scaling.

Distributed deep reinforcement learning for autonomous aerial eVTOL mobility in drone taxi applications

The urban aerial mobility (UAM) system, such as drone taxi or air taxi, is one of future on-demand transportation networks. Among them, electric vertical takeoff and landing (eVTOL) is one of UAM systems that is for identifying the locations of passengers, flying to the positions where the passengers are located, loading the passengers, and delivering the passengers to their destinations. In this paper, we propose a distributed deep reinforcement learning where the agents are formulated as eVTOL vehicles that can compute the optimal passenger transportation routes under the consideration of passenger behaviors, collisions among eVTOL, and eVTOL battery status.

Digitalization of Arctic Logistics Management Systems for Oil Transportation

Today there is a great scientific interest in the development of the Russian Arctic, as one of the most attractive and promising areas in terms of hydrocarbon production potential. Oil production projects in the Arctic shelf are extremely capital intensive. Their successful implementation requires solving a number of tasks to overcome many existing barriers and challenges that oil and gas producers face today. One of such problems is the task of choosing an optimal hydrocarbon transportation route and creating an effective transportation and logistics system for offshore fields. The article gives examples of Arctic projects being implemented today, analyzes the advantages and disadvantages of various methods of oil transportation currently used, and describes an intelligent digital system of Arctic logistics management, the implementation of which is designed to improve the efficiency of transport and logistics system for offshore fields in the Arctic.

ОЦІНЮВАННЯ ЕФЕКТИВНОСТІ ТРАНСПОРТНОГО ПАРКУ ЛОГІСТИЧНОЇ КОМПАНІЇ

The article is devoted to the conceptual issues of evaluation of the efficiency of the logistics company's transport park. The information base of the study is data of the real logistics network of one of the leading logistics companies in Dnipro, which has 42 branches. Based on the capabilities of the Google OR-Tools optimization package, a system of optimal transport routes for different fleet options has been built. According to the results of calculations, the transition from vehicles with higher capacity to lower capacity increases the number of passages and the length of the optimal route. Replacing the fleet of the largest load capacity (20 tons) with the smallest (1 ton) leads to considerable increasing of the optimal route’ length. Less capable vehicles are characterized by lower fuel consumption. But the results of calculating the total cost of implementing optimal routes proves that the transition from more capable to less capable vehicles is not effective. Indirect estimation of the efficiency of the combined fleet was built by gradually replacing of the minimum capacity vehicles in the fleet with the maximum capacity vehicles. For each such variant of the fleet, the optimal route was built, its length was recorded and fuel consumption was estimated. Estimation of fuel consumption was carried out by multiplying the length of mileage of large and small-capacity vehicles by the corresponding fuel consumption rates. Prospects for further research are to verify the results using alternative optimization tools. The results of the analysis indicate the effectiveness of building a transport fleet of logistics company based on heavy-duty vehicles. This approach reduces the number of pendulum routes and minimizes fuel consumption through the use of ring routes.

OPTIMIZATION OF CARGO ROUTES BASED ON THE MODIFIED ANT ALGORITHM

Summary. The article is devoted to solving complex problems of optimization of freight transportation, namely search and determination of the most suitable solution for optimizing (finding a minimum or maximum) the target function (price, accuracy, time, distance, etc.) from a discrete set of possible solutions. The article substantiates the direction of modification of the ant algorithm, an algorithm for routing the implementation of the transport process is formed on the basis of the study of the state and determination of the theoretical throughput of individual sites on the projected routes. As well as an analysis of the effectiveness of classical and modified algorithms on the example of designing optimal routes from the point of departure to the destination and to find the maximum freight route. Among the modern methods for solving the problem of a salesman, an ant algorithm is chosen, since its physical basis – the behavior of ants when searching for food – is the closest to formulating this problem, which determines the optimal route for transportation and its profitability for the company. A mathematical model was constructed, an algorithm was proposed and a flowchart was developed to determine the optimal transportation route based on a modified ant algorithm. A program was developed in the Delphi environment to determine the optimal route by the minimum distance criterion based on the proposed algorithm of the salesman problem. The task of determining the shortest route, which includes regional centers of Ukraine, is connected and a graph of this route is constructed. The optimal route was developed: Kyiv - Zhytomyr - Lutsk - Chernivtsi - Uzhgorod - Lviv - Ivano-Frankivsk - Khmelnytsky - Cherkasy - Zaporizhzhia - Kharkiv - Chernihiv - Nikolaev - Kirovograd - Dnipro - Poltava - Sumy - Vinnytsia - Ternopil - Rivne - Kherson - Odessa - Kyiv, with a total distance of 7,930 km and a freight of 190,710 UAH. A program has been developed in the Delphi environment to determine the optimal route according to the maximum freight criterion of the carrier based on the proposed algorithm of the salesman problem. This task is connected for a network of 22 cities – regional centers of Ukraine, and a graph of the received route was constructed. The optimal route was developed: Kyiv – Mykolaiv – Chernivtsi – Zhytomyr – Khmelnytskyi – Dnipro – Lutsk – Kirovohrad – Rivne – Kherson – Sumy – Ternopil – Chernihiv – Vinnytsia – Poltava – Odesa – Lviv – Kharkiv – Uzhgorod – Zaporizhzhia – Ivano-Frankivsk – Cherkasy – Kyiv, with a total freight for the carrier of UAH 357,800 and a distance of UAH 16,170 km. Justification of optimal routes is quite an important task for the effective operation of logistics companies, since freight transportation is extremely important for the economy of the country and the company and is relevant in the present. According to the results of calculations, technical solutions have been developed to improve the efficiency of the logistics company on the basis of a modified ant algorithm.

Solid Waste Management and Transport Route Optimization Using Geographic Information System in Lagos Metropolis, Nigeria

With an unprecedented population and rapid urbanization, the solid waste collection and transportation has become a major challenge in Lagos metropolis. The main objective of the study was to optimize routes for solid waste collection and disposal using Geographic Information System (GIS) in order to improve solid waste management system in Lagos metropolis. Data on the GIS Network Analyst was used to determine movements between the transfer loading stations and the landfills to determine the collection time, travel distances, optimized routes and alternative routes for solid waste disposal while maximising total solid waste collection and disposal for environmental sustainability. Based on the findings, the study therefore recommends possible interventions such as regular collection of solid waste, proper management of the transfer loading stations and landfills, and that the collection of solid waste should be given more attention because it is important in the development of cities.
 Keywords: Solid wastes, Transportation, Route Optimization, GIS, Lagos metropolis

Удосконалення часткової методики оптимізації маршруту перевезення матеріальних засобів

У статті на основі аналізу системи перевезення матеріальних засобів Збройних Сил України проведено дослідження стосовно удосконалення часткової методики оптимізації маршруту перевезення матеріальних засобів Збройних Сил України.
 На сьогодні існуючі методики носять частковий характер та не враховують нові чинники врахування раціональності та оптимізації маршруту руху, які в сучасних умовах значно впливають на ефективність системи перевезення матеріальних засобів.
 Одним з основних завдань системи перевезення є своєчасність, повнота перевезення та мінімізація витрат, пов’язаних з доведенням матеріального потоку від первинного джерела (виробника, постачальника) до кінцевого споживача (підрозділу).
 У дослідженні щодо оптимізації маршрутів перевезення матеріальних засобів визначається найкоротший шлях, що веде з джерела забезпечення до пункту призначення в зв’язній мережі при заданих відстанях, асоційованих з кожним ребром мережі.
 Дослідження полягає у визначенні оптимального маршруту проходження по мережі між пунктами по пов’язаних з ними дорогах, з мінімальною загальною довжиною пройденого шляху із застосуванням методів мережевого планування.

Optimization of the tourist route by solving the problem of a salesman

The article is devoted to the problem of constructing the optimal transport route of a bus excursion tour of a tour operator according to the minimal length criterion. Transportation expenses are an important part of a bus tour cost, and their minimization is a required condition for route development and planning. To solve this problem, the authors used the tour route calculating method as a kind of transport task, namely the task of the salesman. To solve this problem, one of the varieties of the transport problem, namely the salesman traveling problem, is applied. The essence of the traveling salesman problem is to find the shortest route between cities, if the distances between them are known. The beginning of the route and its end coincide, that is, the route is cyclic. The most popular in Ukraine sightseeing tours of tour operators to the Transcarpathian region are taken for the optimization. A mathematical model of the traveling salesman problem is made to construct an optimal transport route. The solution was found using the Microsoft Excel’s Solver add-in application program package. To solve the problem by this method, it was reduced to a special form and additional variables were introduced. The analysis helped the tour operator to check the existing sightseeing bus routes by the minimal length criterion. The results allowed making assumptions about the need to change some popular routes of Ukrainian tour operators in order to reduce transport costs. The method of bus tours evaluation of tour operators according to the minimal length criterion allows to check the tourist transportation optimality while planning the route and developing their own tourist product. The introduction of modern digital technologies and software to optimize the territorial organization of tourist routes is proposed, which will help tour operators of Ukraine in the design of bus tourist trips to nature and recreational locations in tourist regions. The development of an optimal model for the transportation of tourists on the highways and the reduction of their costs for consumption of transport services will contribute to the development of tourist trips in Ukraine. The necessity of using methods of geolocation of tourist resources for the construction of routes for visiting natural and cultural-historical monuments and tourist centers has been determined. The application of the proposed method will allow tour operators to reduce transport costs and, as a consequence, the total cost of the tourist product.

Model of Determining the Optimal, Green Transport Route among Alternatives: Data Envelopment Analysis Settings

Data envelopment analysis (DEA) is a useful method for determining relative efficiency in many types of businesses, including the transport sector. In line with the European Union’s (EU) policy of sustainable development of transport, external costs become the competitiveness factor of the transport route valorization. Presenting specific DEA settings, the paper aims to show and test a developed model for determining the optimal transport route among alternatives towards the same destination where external cost as a socio-ecological factor is included in DEA, along with transport cost (quantitative factor) and transport time (qualitative factor). In order to adhere to the principles of the least possible energy consumption, the given distance that also included in DEA settings represents the shortest route between the starting point and destination, as a unique and constant output variable. Therefore, the optimal direction selected by the DEA stands for the green route. The capabilities of the DEA, set up in this way within the broader model, are demonstrated in the practical case.

Route Planning with Dynamic Information from the EPLOS System

The paper presents the problem of distribution route planning with dynamic information about sudden customers' needs. Particular attention was paid to dynamic vehicle route planning and its influence on the distance covered by a distribution vehicle. In the article, authors assume that the quick information about customers’ sudden needs is transferred from the EPLOS tool data base. Authors analyze the available literature on transport route optimization and propose a solution to the problem of distribution among customers with sudden needs. In order to present the impact of quick information influence on the distribution route minimization, a simulation model of the vehicle routing problem was generated in the FlexSim environment.

Effect of terrain relief on the transport cost on road of biomass raw materials: Energy conservation study of 9 cities and counties in China

Transport cost on road is an important limiting factor in the development of biomass energy. At present, transport cost on road is typically calculated using the average slope derived from the elevational difference between two points on a 2D road network, but this method ignores terrain relief, which is an important factor that influences road slope and vehicle fuel consumption. This study explores the effect of terrain relief on transport cost on road to provide data support for the optimization of transportation routes for biomass raw materials. By setting sample points at different intervals along a transportation route to accommodate different reliefs, the results showed that terrain relief was positively correlated with the unit distance transport cost on road by truck of biomass raw materials. When the sample interval was less than 500 m, the unit distance transport cost on road decreased rapidly with an increase in sample interval, and the rate of decline in hilly areas was greater than that in plains areas. When the sample interval was greater than 500 m, the unit distance transport cost on road decreased slowly and approached a stable level as the sample interval increased. In hilly areas, the transport cost on road of biomass raw materials and the relief effect were greater than those in plains areas. Therefore, when calculating the transport cost on road of biomass raw materials, we recommend using sample intervals less than 500 m to achieve a more accurate calculation and maintain a relatively small calculation load.

Cost and Scenario Analysis of Intermodal Transportation Routes from Korea to the USA: After the Panama Canal Expansion

This study is aimed at suggesting the most economical transportation route by comparing seven different Korea–US intermodal transportation routes for automotive parts exported to Southeastern USA. To keep up with the global competition of parts makers, which are expanding their markets based on advanced technology and enormous capital, Korean automotive parts makers also need to actively advance their markets overseas. From this point of view, selecting an efficient transport route and transportation modes for overseas export is essential. To this end, the most efficient transportation route from the perspective of total logistics cost was selected by adapting the inventory-theoretic model, using information such as the logistics status of a specific company and the logistics freight rates and transit time for the third quarter of 2019. Thus, the scenario analysis was conducted assuming that variables—namely transportation cost per unit, commodity value, inventory cost and additional conditions such as terminal free time—were modified. Through this study, the optimal transportation route was selected by fully considering and predicting the total logistics cost component and the variability of the major factors.

An evaluation of three DoE-guided meta-heuristic-based solution methods for a three-echelon sustainable distribution network

This article evaluates the efficiency of three meta-heuristic optimiser (viz. MOGA-II, MOPSO and NSGA-II)-based solution methods for designing a sustainable three-echelon distribution network. The distribution network employs a bi-objective location-routing model. Due to the mathematically NP-hard nature of the model a multi-disciplinary optimisation commercial platform, modeFRONTIER®, is adopted to utilise the solution methods. The proposed Design of Experiment (DoE)-guided solution methods are of two phased that solve the NP-hard model to attain minimal total costs and total CO2 emission from transportation. Convergence of the optimisers are tested and compared. Ranking of the realistic results are examined using Pareto frontiers and the Technique for Order Preference by Similarity to Ideal Solution approach, followed by determination of the optimal transportation routes. A case of an Irish dairy processing industry’s three-echelon logistics network is considered to validate the solution methods. The results obtained through the proposed methods provide information on open/closed distribution centres (DCs), vehicle routing patterns connecting plants to DCs, open DCs to retailers and retailers to retailers, and number of trucks required in each route to transport the products. It is found that the DoE-guided NSGA-II optimiser based solution is more efficient when compared with the DoE-guided MOGA-II and MOPSO optimiser based solution methods in solving the bi-objective NP-hard three-echelon sustainable model. This efficient solution method enable managers to structure the physical distribution network on the demand side of a logistics network, minimising total cost and total CO2 emission from transportation while satisfying all operational constraints.

Carbon Emission of Municipal Solid Waste in Shanghai

In recent years, the issue of global warming caused by carbon emissions has attracted the attention of scholars from all walks of life. The amount of carbon emissions caused by urban activities has also been increasing. Especially, the contribution of urban household waste to carbon emissions is very high. It is the second largest global greenhouse gas. Adults are sources of emissions. The research object of this article is Shanghai Municipal Solid Waste, which simplifies the life cycle of domestic waste into two parts: transportation part and treatment part. It uses the provincial GHG inventory production method recommended by IPCC (2006) for the life of Shanghai from 2005 to 2015. Rubbish carries out carbon emission accounting and observes the changing trend of carbon emissions year by year. The results show that the production of domestic garbage in Shanghai has basically stabilized, and the proportion of household garbage disposed by sanitary landfills accounts for the most. The main carbon emissions in the transportation process are automobile vehicle tail gas emissions. The main carbon emissions in the waste treatment process are carbon emissions from sanitary landfills. The carbon emissions from landfill disposal are at a minimum, and the generation of household waste when incinerated and generated can be reduced. For Shanghai, the optimization of transportation routes and the reduction of sanitary landfill disposal of the amount of domestic waste is the most important emission reduction measure.

Path Optimization of Medical Waste Transport Routes in the Emergent Public Health Event of COVID-19: A Hybrid Optimization Algorithm Based on the Immune-Ant Colony Algorithm.

In response to the emergent public health event of COVID-19, the efficiency of transport of medical waste from hospitals to disposal stations is a worthwhile issue to study. In this paper, based on the actual situation of COVID-19 and environmental impact assessment guidelines, an immune algorithm is used to establish a location model of urban medical waste storage sites. In view of the selection of temporary storage stations and realistic transportation demand, an efficiency-of-transport model of medical waste between hospitals and temporary storage stations is established by using an ant colony–tabu hybrid algorithm. In order to specify such status, Wuhan city in Hubei Province, China—considered the first city to suffer from COVID-19—was chosen as an example of verification; the two-level model and the immune algorithm–ant colony optimization–tabu search (IA–ACO–TS) algorithm were used for simulation and testing, which achieved good verification. To a certain extent, the model and the algorithm are proposed to solve the problem of medical waste disposal, based on transit temporary storage stations, which we are convinced will have far-reaching significance for China and other countries to dispatch medical waste in response to such public health emergencies.

Research on Decision-making Method for Allocation of Product Maintenance Spare Parts

Under the current market situation, improving the efficiency and quality of after-sales service has become one of the effective means for improving the competitiveness of an enterprise. In this paper, the cost coefficient method is introduced into the research on decision-making method for allocation of product maintenance spare parts. By analyzing the factors influencing the transportation of maintenance spare parts, a model is established for the allocation cost coefficient of maintenance spare parts. The optimal transportation route of maintenance spare parts is calculated by using A-star algorithm. The optimal allocation scheme is obtained according to the table-manipulation method on linear programming. The feasibility of the model is verified by an example. The method is scientific, reasonable, simple and easy to learn. With strong generalization and operability, the method can effectively improve the allocation efficiency of maintenance spare parts and save the cost of after-sales service.

Optimization of garbage transport routes in West Medan using Clarke & Weigh saving and Floyd Warshall algorithm

Problems of Medan City is the city with the third highest population density in Indonesia. This results in a large quantity of waste generation in the Medan city that must be managed. Limitations of waste transport equipment resulting in the accumulation of waste in various polling stations in the city of Medan so that it needs to be carried out distribution route optimization. Optimization is done by Clarke & Weight Saving and Floyd Warshall Algorithm. Saving matrix method is one method used to schedule the quantity of vehicles taking into account the maximum quantity of vehicles. The Floyd–Warshall algorithm is a simple and widely used algorithm to compute shortest paths between all pairs of vertices in an edge weighted directed graph. It can also be used to detect the presence of negative cycles. Routes generated using the Saving Matrix method successfully save of travel distance of 33.65 km, and using Floyd Warshall successfully save the travel distance of 25.89 km.

Optimization of waste transport routes in Pati Regency using ArcGIS

Based on the Recapitulation Data of the 2017 Pati District Waste from the Sanitation and Gardening Sector of the DPUTR Pati Regency shows that the amount of waste in Pati Regency is 3,082 tons / day. Meanwhile, the amount of waste transport to sanitary landfill only reaches 320 tons/day. Based on data from the Sanitation Strategy in Pati Regency 2015, Pati Regency Government was able to generate waste transportation service in urban areas by 7.17% and rural areas by 0.87%. This issue not comparable to the area of 1.580,37 km2 with a population density of 785 people/km2. The purpose of this study is to find the optimal value of waste transportation from the existing TTS point and New TTS points to the sanitary landfill by considering the distance and travel time with ArcGIS to improve waste transportation services in Pati Regency. Data collection methods in this study are: first, primary survey with direct interviews with Public Works Agency and Environmental Agency in Pati Regency about waste transportation systems at the polling station point. Second, the secondary surveys related to waste transportation system data namely density points for waste generation, number of garbage trucks and other data related to waste transportation systems. The results show that ArcGIS can help Optimize Travel Time by 39,04% and Optimization of Mileage by 37,38% and the volume of waste transported to reach 2.19% from Temporary Trash Shelter to Landfill.

Waste Transportation Route Optimization in Malang using Network Analysis

Malang has a projection population of 861,414 people in 2018. This big population would cause waste generation that is increasing every day. Waste generation was recorded at the amount of up to 646.07 tonnes/day just from Malang in 2018. However, waste transported to landfill was only 516.84 tonnes/day. It means that the load factor was only 84.73%. Waste transportation problems come from various factor. Malang had only 68 temporary waste storage (TPS) that were spread in the city. This number of TPS was not commensurate with waste generation that was generated every day. The limited number of trucks was another issue considering Malang only had 35 trucks capable of making three trips per day. Limited number of trucks and TPS has led to a bad situation for transporting waste. As a result, many wastes were left behind in TPS. Therefore, it is necessary to analyze the best route for the trucks sso that the waste route can be optimized using network analysis in ArcGIS. This study assessed one route of a truck which had the longest distance (TPS Tunggul Wulung) with a total of 60.2 km at a time that it reached in 113.8 minutes. The result of the network analysis method with ArcGIS showed that the total distance declined to 36.2 km. This indicates that the alternative route shown by the shortest distance method has been able to reduce the existing distance for waste transportation route by 24 km. This certainly resulted in the decline in travel time for ± 39 minutes/day. This indicates that the existing routes can be optimized by alternative route network analysis in ArcGIS.

Intelligent decision support systems for determining tour bus route with time windows: A metaheuristic approach

The transportation routing problem is a very popular field in operations research and management science area. Many previous researches are still continuing to develop model and algorithm to produce the best transportation route optimization in various research objects. Technology has enabled the development of the intelligent decision support system (I-DSS) to optimize transportation route. Although technology has evolved, there are still few researches that build I-DSS software to minimize transportation distance and fuel consumption, especially using the metaheuristic approach. Thus, this paper aims to develop I-DSS software to minimize fuel consumption and travel distance by considering time-windows constraint using metaheuristic approach. The software can receive input dynamically to evaluate and select the best transportation route. The results of this software have been tested using real historical data from one of tour and travel company in Indonesia. The company provides travel services using a bus to visit several tourist attractions based on the opening hours of the destinations. I-DSS software output shows that the travel distance is 25.64% more efficient than the current real conditions. In addition, the fuel consumption produced by I-DSS is better than the actual conditions, which is 17.35% more efficient.