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Multipopulation Ant Colony System With Knowledge-Based Local Searches for Multiobjective Supply Chain Configuration

Supply chain management (SCM) is a significant and complex system in a smart city that requires advanced artificial intelligence (AI) and optimization techniques. The multiobjective supply chain configuration (MOSCC) in SCM is to set the optimal configurations for supply chain members to minimize both the cost of goods sold ( CoGS ) and the lead time ( LT ). Although some algorithms have been proposed for the MOSCC, they do not make the best use of the problem-related knowledge and cannot perform well on the large-scale instances with many members and configuration options. Therefore, this article proposes a multipopulation ant colony system with knowledge-based local searches (MPACS-KLSs). First, the multiobjective algorithm is based on the multiple populations for multiple objectives framework. Two ant colonies are used to separately minimize CoGS and LT , which helps to search in the biobjective space sufficiently. Second, with the considerations of the problem-related knowledge, a priority-based solution construction method, a rank-based heuristic strategy, and an objective-oriented global pheromone updating strategy are proposed. Third, to speed up the convergence, especially for large-scale MOSCC instances, two knowledge-based local searches are designed to minimize CoGS and LT of solutions, respectively. Exhaustive experiments are conducted on both the instances from the real life and the randomly generated instances with different problem scales. The results show that MPACS-KLS is superior to the contestant algorithms, especially on the large-scale MOSCC instances, which significantly extends the AI and optimization techniques in practical applications of the smart city.

Ketersediaan

Informasi Detail

Judul Seri

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION; Vol.26 No.3 June 2022

No. Panggil

-

Penerbit

: .,

Deskripsi Fisik

p. 512-526

Bahasa

English

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

MULTIOBJECTIVE OPTIMIZATION
SMART CITY
ANT COLONY SYSTEM (ACS)
KNOWLEDGE-BASED LOCAL SEARCHES (KLSS)
SUPPLY CHAIN CONFIGURATION (SCC)

Info Detail Spesifik

DOI: 10.1109/TEVC.2021.3097339

Pernyataan Tanggungjawab

Xin Zhang, Zhi-Hui Zhan, Wei Fang, Pengjiang Qian, Jun Zhang

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