Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/6649
Title: Increasing efficiency of on-line shopping by optimizing the staff schedule
Authors: Bikov, Dusan
Dvoriashyna, Mariia
Ertugrul, Ümit
Kresoja, Milena
Koceva Lazarova, Limonka
Repetto, Rodolfo
Stojancevic, Tijana
Stojanova, Aleksandra
Stojkovic, Natasa
Stojkovska, Irena 
Veneva, Milena
Ying, Fabian
Zlatanovska, Biljana
Issue Date: 18-May-2018
Publisher: Gran Sasso Science Institute
Conference: ESGI136, L'Aquila, May 14-18 2018
Abstract: COOP Drive is an on-line shopping system recently started by COOP Liguria. Customers place their orders on-line, which are then processed by employees and collected at the time chosen by the customer. The problem proposed by COOP consists of two main parts: i) optimizing the staff schedule in COOP Drive ii) understanding if and to what extent such a schedule could be improved if orders were placed in advance. Providing a good schedule is very important for employees to reach an adequate level of satisfaction. According to the proposed problem from the on-line food shopping service, our aim was to make optimal staff scheduling such that each employee has `constant' working hours, i.e. that they work the same number of hours each working day. We introduce three different complementary models as approaches for the solution. The fi rst model is based on scheduling approach, which we solved for a simplifi ed scenario and is aimed to answer the first part of the problem. For the second question, we adopted two different approaches: an agent-based model that aims to understand the number of employees needed to process the order history and a worker placement model, that is developed to predict the number of employees required every hour to process the orders. These two models suggest that no signi ficant reduction of employees can be obtained by placing the orders in advance, however, signi ficant bene fit is achieved in terms of homogeneity of the schedule.
URI: http://hdl.handle.net/20.500.12188/6649
Appears in Collections:Faculty of Natural Sciences and Mathematics: Conference papers

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