A Type of Transportation Problem to be Solved Following the Time Criterion and Considering Vehicle Features

The formulation of classical minimax transport-type problems involves the search for an optimal transportation plan considering only time of delivery of resources. The inevitable additional costs of processing resources at the origin and destination are usually not considered. This approach is fully justified given incommensurability of delivery times of resources along available routes and times of preliminary/subsequent processing of resources. At the same time, in a number of practical problems, the time spent on loading/unloading (for example, when organizing loading of packaged mineral fertilizers from port warehouses onto ships) can be of significant importance. In such cases, when searching for an optimal transportation plan, it is necessary to take into account not only travel times of vehicles used along the set routes, but also the costs of loading and unloading operations, considering the number of available vehicles and their characteristics, for example, payload.In this regard, the objective of the study is not only to develop a method for calculating the optimal transportation plan, but also a method for distributing vehicles, considering their number and features.At the same time, another no less important objective of the study is to substantiate the application of the method of successive reduction of residuals, considering the form of the objective function, which considers not only the main parameters of classical minimax transport-type problems, but also the quantitative characteristics of vehicles involved in the transport operation. It is fundamentally important that the use of the method of successive reduction of residuals determines the polynomial computational complexity of the algorithm, which makes it possible to use it in the operational solution of problems of practical dimension.To solve the problem of distributing available vehicles according to the origin points, considering payload of vehicles, it is proposed to use the method of dynamic programming. An illustrative example of distribution of delivery vehicles, adapted for the use in MS Excel, is considered.

The Optimization of Transportation Costs in Logistics Enterprises during the Covid-19 Pandemic

The Covid-19 pandemic has had a significant impact on every industry globally, especially the transportation industry being severely disrupted. With people's travel demand at an all-time low, maintaining the country's transportation infrastructure is crucial to ensure the movement of essential goods. However, the Vietnamese government’s decision to apply social distancing measures to limit and prevent the spread of the disease has generated extreme challenges in the freight transport industry, which have harmed the Vietnamese economy by restricting levels of business activity, causing the movement and distribution of essential commodities to be halted. Based on the practical needs of transportation enterprises, this study proposes a low-cost freight allocation strategy using mix-integer linear programming approaches to ensure an efficient operation for businesses in order to resume normal operations in the context of the Covid-19 epidemic's complex development. The research focuses on developing a mathematical model with an objective function that minimizes total cost and associated constraints. The findings of the study point to the development of a solution that solves businesses problems in determining the optimal transportation plan and assist in making decisions on allocating goods to suitable locations, ensuring the quantity of serving the needs of each district in Ho Chi Minh City, minimizing transportation time while still saving costs. Furthermore, the article aids a decision-making process for other transportation industries.

A METHOD FOR SOLVING THE CANONICAL PROBLEM OF TRANSPORT LOGISTICS IN CONDITIONS OF UNCERTAINTY

Subject.The canonical task of transport logistics in the distributed system "suppliers - consumers" is considered. Goal. Development of an accurate algorithm for solving this problem according to the probabilistic criterion in the assumption of the random nature of transportation costs has been done. Tasks. 1. Development of an exact method for solving the problem of finding a plan that minimizes the total cost of transportation in conditions when their costs are given by their distribution densities. 2. Development of a method for solving the problem when the distribution density of the cost of transportation is not known. Methods. A computational scheme for solving the problem is proposed, which is implemented by an iterative procedure for sequential improvement of the transportation plan. The convergence of this procedure is proved. In order to accelerate the convergence of the computational procedure to the exact solution, an alternative method is proposed based on the solution of a nontrivial problem of fractional nonlinear programming. The method reduces the original complex problem to solving a sequence of simpler problems. The original problem is supplemented by considering a situation that is important for practice when, in the conditions of a small sample of initial data, there is no possibility of obtaining adequate analytical descriptions for the distribution densities of the random costs of transportation. To solve the problem in this case, a minimax method is proposed for finding the best transportation plan in the most unfavorable situation, when the distribution densities of the random cost of transportation are the worst. To find such densities, the modern mathematical apparatus of continuous linear programming was used. Results. A mathematical model and a method for solving the problem of transport logistics in conditions of uncertainty of the initial data are proposed. The desired plan is achieved using the solution of the fractional nonlinear programming problem. Conclusions: The problem of forming a transportation plan is considered, provided that their costs are random values. Also, a method for solving the problem of optimization of transportation for a situation where the density of distribution of random cost cannot be correctly determined is considered.

DEVELOPMENT OF METHODS FOR SUPPLY MANAGEMENT IN TRANSPORTATION NETWORKS UNDER CONDITIONS OF UNCERTAINTY OF TRANSPORTATION COST VALUES

The problem of transport management in a distributed logistics system "suppliers – consumers" is considered. Under the assumption of a random nature of transportation costs, an exact algorithm for solving this problem by a probabilistic criterion has been developed. This algorithm is implemented by an iterative procedure for sequential improvement of the transportation plan. The rate of convergence of a computational procedure to an exact solution depends significantly on the dimension of the problem and is unacceptably low in real problems. In this regard, an alternative method is proposed, based on reducing the original problem to solving a nontrivial problem of fractional-nonlinear programming. A method for solving this problem has been developed and substantiated. The corresponding computational algorithm reduces the fractional-nonlinear model to the quadratic one. The resulting problem is solved by known methods. Further, the original problem is supplemented by considering a situation that is important for practice, when in the conditions of a small sample of initial data there is no possibility of obtaining adequate analytical descriptions for the distribution densities of the random costs of transportation. In this case, the available volume of statistical material is sufficient only to estimate the first two moments of unknown distribution densities. For this marginal case, a minimax method for finding the transportation plan is proposed. The first step is to solve the problem of determining the worst distribution density with the given values of the first two moments. In the second step, the transportation plan is found, which is the best in this most unfavorable situation, when the distribution densities of the random cost of transportation are the worst. To find such densities, let’s use the modern mathematical apparatus of continuous linear programming

Green and Safety School Regional Program to Sustainable Development Using Limited Traffic Zone

The traffic around the schools is one of the worst events for sustainability. The effects are heavy for pollution, for safety deriving from multiplied walk-car cross, for autonomy reduced for student. This paper discusses on Green and Safety School program that realizes Limited Traffic Zones (LTZ) around the schools. Calabria Region has made political and technical decisions oriented towards sustainable development, according to international, European and national targets: by Regional Transportation Plan (RTP), the Region has implemented several ways for realization of the planned measures relative to the urban centres defined by Action 2 Urban areas; by School Plan and program the Region has invested to reduce the vulnerability of school building. The aim of Green and Safety School program is offering a new and never developed field for social, economic and environmental sustainability in urban areas and to propose a strategy for traffic control near schools from basic considerations regarding a problem common of all cities around the world. This program derives from the results obtained with two different previously implemented programs: one relative to the rebuild of school who reduce risk (Scuola Sicura) and another one to the City logistics (leaving from RTP). From an advanced synthesis of these 2 programs born the very new use of LTZ. Green and Safety School is oriented to guarantee green areas and to reduce risk outside school. Even if the program leaves before COVID-19, it assumes significant importance to guarantee social distancing.

The criterion of arising motion conflict of unmanned vehicles during implementing transportation plan in intelligent urban passenger transportation system

The proposed article is devoted to the description of an intelligent urban passenger transport system based on unmanned electric vehicles, sequentially moving along a separate line. This system is a passenger transport system of a new urban mobility, formed under the influence of social conditions generated by high population density in cities, that suppose the development of pedestrian zones and ecological modes of transport, "transport as a service", etc. In this historical context, public transport systems acquire special relevance. The described transport system belongs to intelligent systems, since it is capable of functioning in autonomous mode without human intervention, adaptively responding to changes in the dynamics of the flow of passengers during the day. Passengers are transported by electric cars, which can be combined into cassettes according to the principle of road trains based on the transportation plan drawn up by the intelligent center of the transport system according to the matrix of correspondences, filled in taking into account the incoming requests for service from passengers. When drawing up a transportation plan, the algorithms of the transport system give preference to transportation according to the "source-destination" principle, that is, when the passenger goes to the destination with a minimum number of intermediate stops, and ideally without them. The paper formulates also a criterion of arising of a conflict in the movement of vehicles, which allows to identify situations when an electric vehicle driving in front can detain vehicles following after. The work has relevance because the criterion will allow to make adjustments in the schedule of movement of vehicles and exclude the loss of time and energy that carries the transport system during braking and acceleration of electric cars, as well as to reduce waiting time and travel of passengers.