A multi-objective decision-making model to select waste electrical and electronic equipment transportation media

被引:34
|
作者
Achillas, Ch. [1 ]
Aidonis, D. [2 ]
Vlachokostas, Ch. [3 ]
Moussiopoulos, N. [3 ]
Banias, G. [1 ]
Triantafillou, D. [2 ]
机构
[1] Int Hellen Univ, Sch Econ & Business Adm, Thermi 57001, Greece
[2] Alexander Technol Educ Inst, Dept Logist, Branch Katerini, Katerini 60100, Greece
[3] Aristotle Univ Thessaloniki, Lab Heat Transfer & Environm Engn, Thessaloniki 54124, Greece
关键词
WEEE; Multicriteria optimisation; Multiple objective linear programming; Reverse logistics; Transportation; SUPPLY-CHAIN MANAGEMENT; REVERSE LOGISTICS;
D O I
10.1016/j.resconrec.2012.01.004
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Electrical and electronic equipment (EEE) materials possess considerable economic value. together with potential toxicity. The rapidly increasing sales of EEE worldwide, constitutes the rational management of waste electrical and electronic equipment (WEEE) a matter of critical importance, both in economic and environmental terms. Taking into account that reverse logistics is one of the most important parameters in the management of waste equipment, it is particularly important for the manufacturers to control relevant cost in order to be market competitive. One of the most critical decisions regarding reverse logistics costs is the type of carrier to be used. To this end, this paper presents a multicriteria optimisation model for multi-type carriers of WEEE, based on multiple objective linear programming (MOLP). The main goal of a MOLP model is the weighted optimisation of different objectives. In our case. the proposed MOLP approach minimises total logistics costs, consumption of fossil fuel and production of emissions due to transportation of WEEE with the use of different types of containers. The model embodies existing infrastructure in collection points and recycling facilities and targets towards optimisation of the reverse logistics network for a single planning period by taking into account both economic and environmental aspects of the problem under study. (c) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:76 / 84
页数:9
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