Random Energy-Efficient Models for Sustainable Facility Location Subject to Carbon Emission, Economical, Capacitated and Regional Constraints | Zendy

Hongfei Jia | Zendy; Yingjun Xu | Zendy; Guangdong Tian | Zendy; Mengchu Zhou | Zendy; June Zhang | Zendy; Honghao Zhang | Zendy

Open Access

Random Energy-Efficient Models for Sustainable Facility Location Subject to Carbon Emission, Economical, Capacitated and Regional Constraints

Author(s) -

Hongfei Jia,

Yingjun Xu,

Guangdong Tian,

Mengchu Zhou,

June Zhang,

Honghao Zhang

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2870596

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

An uncertainty facility location allocation (FLA) problem is a complex nonlinear optimization problem. Currently, researchers have discussed the stochastic cost/profit issues of FLA. However, rising energy conservation awareness and environmental concerns, energy-efficientcy and low-carbon emission should be regarded as key criteria in solving it. To do so, this paper presents a new FLA problem from a sustainable development point of view. By taking a typical facility service enterprise as a case, a new stochastic energy-efficient FLA model subject to carbon emission, economical, capacitated, and regional constraints is formulated. Then, stochastic simulation and scatter search are integrated as an intelligent algorithm to resolve it. Some examples are demonstrated to prove the availability of the proposed model and solution algorithm.

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