Knowledge and Behavior-Driven Fruit Fly Optimization Algorithm for Field Service Scheduling Problem with Customer Satisfaction

Complexity 2021:1-14 (2021)
  Copy   BIBTEX

Abstract

The field service scheduling problem is the key problem in field services. Field service pays particular attention to customer experience, that is, customer satisfaction. Customer satisfaction described by customer behavior characteristics based on the prospect theory is considered as the primary optimization goal in this paper. The knowledge of the insertion feasibility on the solution is analysed based on the skill constraint and time window. According to the knowledge, an initialization method based on the nearest heuristic algorithm is constructed. Based on the prior knowledge of the FSSP and the endowment of the Fruit Fly Optimization Algorithm, two operators are defined according to the matrix encoding method. Based on these two operators, three search strategies are then proposed, and the smell-based search strategy and vision-based search strategy for the FOA are redesigned. To verify the performance of the algorithms, the proposed operators and strategies are tested and analysed in the well-known benchmark. Through comparison with the state-of-the-art algorithms, the results show that the proposed HFOA is an effective and efficient method to solve the FSSP with customer satisfaction.

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 92,227

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Analytics

Added to PP
2021-02-04

Downloads
7 (#1,392,075)

6 months
3 (#984,770)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

Citations of this work

No citations found.

Add more citations

References found in this work

No references found.

Add more references