Literature DB >> 33684758

Inexact inventory-theory-based optimization of oily waste management system in shoreline spill response.

Zhikun Chen1, Chunjiang An2, Xiujuan Chen3, Elliott Taylor4, Ashutosh Bagchi1, Xuelin Tian1.   

Abstract

The oily waste generated from the cleanup operations during shoreline spill response can result in challenging environmental and socioeconomic problems. In this study, an inexact inventory-theory-based optimization model (ITOM) for oily waste management during shoreline spill response was developed to support the spill management team. The most appropriate facilities and optimal waste allocation scheme under uncertainty can be selected to achieve minimum total system cost. To satisfy the demand of oily waste treatment, these oily waste management facilities can be selectively opened depending on the situation. In the combination with the economic order quantity model of inventory theory, the developed model can provide the optimal solutions of batch size and order cycle for treatment facilities to minimize the inventory cost. A case study was used to demonstrate the application of ITOM. The obtained solutions include the facilities selection and waste allocation for waste collection and destocking stages under different risk levels. These solutions can provide a good guideline with managers to analyze the trade-offs between system cost and constraint-violation risks. The developed model has high application potential as a job-aid tool to manage the oily waste generated from oiled shoreline cleanup operations.
Copyright © 2021 Elsevier B.V. All rights reserved.

Keywords:  Oil spill; Oily waste management; Optimization and uncertainties; Response support; Shoreline cleanup

Year:  2021        PMID: 33684758     DOI: 10.1016/j.scitotenv.2021.146078

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  Construction and optimization of inventory management system via cloud-edge collaborative computing in supply chain environment in the Internet of Things era.

Authors:  Hailan Ran
Journal:  PLoS One       Date:  2021-11-03       Impact factor: 3.240

  1 in total

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