Integrated optimisation of consolidation and stowage planning of steel coil ships using differential evolution

Abstract

Consolidation plan (CP) and stowage plan (SP) of coil ships are to assign steel coils onto ships and decide specific loading location for each coil, respectively, which are two correlative and adjacent plans in the finished product logistics of iron and steel industry. In this paper, we focus on the problem of making an integrated plan of CP and SP (C&SPP), which is important and rarely studied, to try to achieve systematic optimisation from the perspectives of the product terminal, shipping companies, and customers, simultaneously. First, according to the practical situation, an integer programming (IP) model is established to optimise ship loading, transportation timeliness, and operation efficiency. Then, to improve calculating efficiency, the IP model is simplified (SIP) by reducing the dimensions of variables. After that, based on the problem features and algorithm behaviour, an improved differential evolution algorithm is proposed in which an element-dependent strategy is designed to set control parameter, a guided operator is constructed to generate mutant individual and an iteration-based mechanism is introduced to dynamically adjust the parameter and mutation strategy, respectively. Finally, extensive experiments are carried out to evaluate the proposed method, and the numerical results demonstrate its effectiveness in solving practical scale C&SPP.

Keywords:

• Differential evolution
• discrete optimisation
• iron and steel industry
• ship consolidation plan
• ship stowage plan

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplemental data

Supplemental data for this article can be accessed at https://doi.org/10.1080/00207543.2020.1722323.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This research was partly supported by the Fund for Innovative Research Groups of the National Natural Science Foundation of China [grant number 71621061], the Major International Joint Research Project of the National Natural Science Foundation of China [grant number 71520107004], the Major Program of National Natural Science Foundation of China [grant number 71790614], the 111 Project (B16009), the Fundamental Research Funds for the Central Universities (N170407003), the Fundamental Research Funds for the Central Universities (N2004003), and the Zhejiang Provincial Natural Science Foundation of China (LQ13G020010).