Managing competitive municipal solid waste treatment systems: An agent-based approach

被引:27
作者
He, Zhou [1 ,2 ]
Xiong, Jie [1 ]
Ng, Tsan Sheng [1 ]
Fan, Bo [3 ]
Shoemaker, Christine A. [1 ,4 ]
机构
[1] Natl Univ Singapore, Dept Ind Syst Engn & Management, 1 Engn Dr 2, Singapore 117576, Singapore
[2] Natl Univ Singapore, NUS Environm Res Inst, 5A Engn Dr 1, Singapore 117411, Singapore
[3] Shanghai Jiao Tong Univ, Sch Int & Publ Affairs, 1954 Huashan Rd, Shanghai 200030, Peoples R China
[4] Natl Univ Singapore, Dept Civil & Environm Engn, 1 Engn Dr 2, Singapore 117576, Singapore
基金
美国国家科学基金会; 新加坡国家研究基金会;
关键词
Simulation; Agent-based model; Municipal solid waste treatment system; Market competition; Simulation-based optimization; MANAGEMENT; MODEL; STRATEGIES; LOCATION; PRIVATE; MARKET;
D O I
10.1016/j.ejor.2017.05.028
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Private sector participation in municipal solid waste (MSW) management is increasingly being applied in many countries recently. However, it remains a largely unexplored issue whether different self-interested treatment operators can co-exist in an economically feasible and sustainable manner. To help the policy maker s understand and manage competitive MSW treatment systems, this paper proposes an agent based waste treatment model (AWTM) that consists of four types of agents, namely the refuse collector, specialized treatment unit (STU), the general treatment unit (GTU), and the regulator. An estimation and-optimization approach is developed for profit-maximizing agents to set optimal gate fee and vie for specific waste in low-information competition. Based on the Singapore case, the experimental results imply that if the regulator deliberately promotes the STUs by intervening in waste allocation, the GTU could give up competing for the waste and greatly increase its gate fees as retaliation. Besides, driven by the increasing gate fee of the GTU, the STUs conservatively raise their gate fee; while the GTU will be the major beneficiary in the AWTM. Finally, to identify the optimal mixed policy under predefined constraints, the AWTM is integrated into a simulation-based optimization problem, which is solved by a genetic algorithm. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:1063 / 1077
页数:15
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