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Model of operational planning of freight transportation by tram as part of a green logistics system

Shramenko Natalya, Merkisz-Guranowska Agnieszka, Kiciński Marcin, Shramenko Vladyslav

Archives of Transport

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2022

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Vol. 63, iss. 3

113--122

EN

The introduction of environmentally friendly technologies is becoming increasingly necessary to combat global warming and air pollution in cities. The concept of ecologistics is seen as an effective approach to the management of materials and related flows in order to reduce environmental and economic damage to the environment. The sustainable development of green supply chains is based on the use of environmentally friendly types of vehicles, reduction of energy and other resources consumption, optimization of transport and technological processes in delivery systems. As part of the development of green supply chain, it is proposed to transport goods by freight trams, which eliminates the need for heavy trucks in the city, improves traffic conditions and reduces the environmental impact of transport. The research was conducted for the city of Poznan. The distribution system of the city of Poznan operates in conditions of stochastic demand for deliveries from clients and the risk of lack of sufficient supplies in distribution centers. To take into account the specificity of the distribution system of cargo delivery in conditions of uncertainty and risk, a simulation model of the organization of the material flows within the transport system of the city of Poznan has been proposed. The result of simulation is the optimal assignment of clients to the distribution centers, as well as the value of total mileage with the load, which is a random variable. It is assumed that the random variable is distributed according to the normal distribution law. The results were calculated and compared for two variants, i.e. for constant demand and sufficient quantity of cargo in distribution centers, and for variable demand and uncertainty conditions, e.g. insufficient cargo quantity in distribution centers. The purpose of the paper is to develop a simulation model for planning supplies of small consignments of goods by trams implementing green logistics concept with variable demand for transportation. After a short introduction of the problem, the literature review related to the concept of green logistics and requirements of transport and distribution system are presented in section 2. In section 3, the research problem and research methodology are described. Section 4 provides the results of assignment of clients to distribution centers. The paper ends with concluding remarks.

2

Forming delivery routes while processing the stochastic flow of requests for forwarding services

Naumov V.

Transport Problems

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2017

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T. 12, z. 4

73--82

EN

Formation of rational delivery routes is the main way to increase the effectiveness of client services for freight forwarding companies. The main part of the requests for transport services comes from occasional (non-constant) clients. The set of those requests forms a stochastic flow. For stochastic requests flow, the delivery routes are formed in the process of the requests receipt. Therefore, the standard approaches for merging of requests from multiple clients into routes, based on linear programming techniques, cannot be used in such conditions. An algorithm of formation under the stochastic demand conditions of such delivery routes, which allow servicing of two or more shippers, is proposed in the paper. The author has developed a specialized software to support decisions made by dispatchers of forwarding companies.

3

Poziom obsługi popytu i stopień ilościowej realizacji zamówień dla różnych rozkładów prawdopodobieństwa popytu

Bieniek M.

Logistyka

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2015

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nr 4

81--89

PL

W pracy rozpatrywane są możliwości wyznaczenia poziomu obsługi klienta w modelach zarządzania zapasami z losowym popytem. Rozważane są trzy typowe rozkłady popytu, mianowicie rozkłady ciągłe: rozkład normalny i rozkład gamma oraz dyskretny rozkład Poissona. Dla tych rozkładów przytoczone są i uproszczone wzory na obliczenie poziomu obsługi popytu I stopnia ilościowej realizacji zamówień. Do wyznaczenia tych wielkości konieczna jest znajomość rozkładu popytu w cyklu uzupełniania zapasu. Badana jest możliwość znalezienia rozkładu popytu w cyklu ze znanego rozkładu popytu w czasie. Podany jest również przykład obliczeniowy.

EN

In the paper the possibility of deriving certain measures of service level in the classical stochastic inventory models is studied. The most popular probabilistic demand distributions are considered, namely continuous normal and gamma distribution and discreet Poisson distribution. For the mentioned distributions the probability of no stock out called cycle service level and the fill rate are cited and simplified. In order to compute these quantities the knowledge of the demand distribution in the lead time is necessary. The possibility of calculation of the lead time distribution given the demand distribution in time is also considered. Finally some computational examples are presented.

4

Stochastic demand in inventory location

Bieniek M.

Logistyka

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2014

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nr 4

EN

In this paper we consider the location inventory model which centralizes or decentralizes the stock. In this model we have to choose between the location of inventory in the regional warehouses or the location in the central warehouse. The choice is done due to minimum the holding costs of the safety stock and also the minimum of supply costs. The important aspect is that the customers can represent the stochastic demands on the inventory items. Additionally, the complex analysis of possible probabilistic demands' distributions is conducted. Some special cases of the model for normally, Poisson and exponentially distributed demands are also studied.

PL

W pracy rozważany jest model lokalizacji zapasu, który centralizuje albo decentralizuje zapas. W tym modelu wybierana jest lokalizacja zapasu jako jedna z dwóch możliwych: w magazynach regionalnych lub w magazynie centralnym. Wybór jest dokonany na podstawie kryterium minimalizacji kosztów utrzymania zapasu zabezpieczającego. Ważnym aspektem tego modelu jest uwzględnienie stochastyczności popytu klientów. Dodatkowo przeprowadzona jest kompleksowa analiza możliwych rozkładów popytu. Ponadto przedstawiona jest postać modelu dla kilku szczególnych przypadków gdy popyt ma rozkład normalny, Poissona lub wykładniczy.

5

Service level in model of inventory location with stochastic demand

Bieniek M.

Archives of Transport

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2014

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Vol. 31, iss. 3

7--21

EN

In this paper we consider the influence of the safety factor on the decision of the inventory location. This decision is done based on the model which centralizes or decentralizes the safety stock. In this model we have to choose between the location of the inventory in the regional warehouses or the location in the central warehouse. The decision is made due to the minimizing the holding costs and the supply costs of the safety stock from the central warehouse to the customer. The main assumption is that the customers have the stochastic demands on the inventory items. Moreover, the customers’ demands have the known distribution with the known parameters. The complex analysis of the influences of possible probabilistic demands' distributions on the safety factors is conducted. The numerical computations for the safety factors used in the facility location model are also presented. In numerical examples we take into considerations the demands’ distributions the most often used in practice like the normal, the Poisson, the Gamma and the exponential distribution. Some graphs for the safety factors of these distributions are also drawn. Moreover for the mentioned demands’ distributions the model of the safety stock location depends on the specific factors. Among other things these factors are the mean and the variance of the demand, the number of the regional warehouses, the assumed service level, and some cost factors like the holding costs and the transportation costs. Some graphs which illustrated the dependence of the model elements on some listed before parameters are presented and their influence on the location decision is studied also.