TY - GEN

T1 - Algorithm for Customers Loss Minimization with Possible Supply Chain Disruption

AU - Lezhnina, Elena

AU - Balykina, Yulia

AU - Lepikhin, Timur

N1 - Lezhnina E., Balykina Y., Lepikhin T. (2020) Algorithm for Customers Loss Minimization with Possible Supply Chain Disruption. In: Sukhomlin V., Zubareva E. (eds) Convergent Cognitive Information Technologies. Convergent 2018. Communications in Computer and Information Science, vol 1140. Springer, Cham

PY - 2020

Y1 - 2020

N2 - Continuous development of companies in various sectors of the economy has led to an expansion of the processes they implement. With the increase in the number of logistic processes of the company, there is a need for their optimization, with a subsequent reduction in the costs of their provision. Logistic costs can reach up to forty-five percent of the company’s general administrative expenses. As of today, there are many approaches to setting and solving the problem for optimization of logistics systems. In this paper, the authors suggest a set of different strategies for selecting suppliers in the market, taking into account a number of constraints, in particular, the supplier’s required reliability, as well as the goods pricing strategy, provided that such goods are competitive. The main objective of the research is to solve the problem of the optimal choice of the quantity of goods in the order with supplier losses minimization. The goal is achieved by choosing the optimal or the so-called economical order size, at which the supplier’s losses will be minimal. To determine the optimal order size, a modified Harris-Wilson formula for the economic order quantity is used. Two types of the problem are considered: a model in the absence of supply disruption and a model with probable supply disruptions. Scenarios of a customer’s behavior are suggested for possible supply disruptions, such as the supplier equipment failure or transportation problems. Using the proposed algorithm, the customer can develop a relevant stock forming strategy.

AB - Continuous development of companies in various sectors of the economy has led to an expansion of the processes they implement. With the increase in the number of logistic processes of the company, there is a need for their optimization, with a subsequent reduction in the costs of their provision. Logistic costs can reach up to forty-five percent of the company’s general administrative expenses. As of today, there are many approaches to setting and solving the problem for optimization of logistics systems. In this paper, the authors suggest a set of different strategies for selecting suppliers in the market, taking into account a number of constraints, in particular, the supplier’s required reliability, as well as the goods pricing strategy, provided that such goods are competitive. The main objective of the research is to solve the problem of the optimal choice of the quantity of goods in the order with supplier losses minimization. The goal is achieved by choosing the optimal or the so-called economical order size, at which the supplier’s losses will be minimal. To determine the optimal order size, a modified Harris-Wilson formula for the economic order quantity is used. Two types of the problem are considered: a model in the absence of supply disruption and a model with probable supply disruptions. Scenarios of a customer’s behavior are suggested for possible supply disruptions, such as the supplier equipment failure or transportation problems. Using the proposed algorithm, the customer can develop a relevant stock forming strategy.

KW - Game theory approach

KW - Loss minimization

KW - Supply chain disruption

UR - http://www.scopus.com/inward/record.url?scp=85081063843&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/c3221c4a-ce45-347a-94d8-a733b4cec510/

U2 - 10.1007/978-3-030-37436-5_12

DO - 10.1007/978-3-030-37436-5_12

M3 - Conference contribution

AN - SCOPUS:85081063843

SN - 9783030374358

T3 - Communications in Computer and Information Science

SP - 142

EP - 149

BT - Convergent Cognitive Information Technologies

A2 - Sukhomlin, Vladimir

A2 - Zubareva, Elena

PB - Springer Nature

CY - Cham

T2 - 3rd International Scientific Conference on Convergent Cognitive Information Technologies, Convergent 2018

Y2 - 29 November 2018 through 2 December 2018

ER -