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首页> 外文期刊>Journal of Environmental Management >Landfill space consumption dynamics in the Lower Rio Grande Valley by grey integer programming-based games
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Landfill space consumption dynamics in the Lower Rio Grande Valley by grey integer programming-based games

机译：基于灰色整数编程的游戏在下里奥格兰德河谷的垃圾填埋空间消耗动态

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摘要

The Lower Rio Grande Valley (LRGV) region in South Texas emerges as a warehouse and transportation center between Central America and the US with positive growth impacts due to the North American Free Trade Agreement (NAFTA). In 10 years time, a 39.8% population increase has resulted in a 25% boost in solid waste per capita disposal rate in the region. A landfill space shortage drives a need for landfill operators to understand their optimal management strategies in this highly-competitive market. Initially, a strategic plan for optimal solid waste pattern distribution minimizes net costs for cities. This is accomplished through a grey integer programming algorithm that encapsulates all uncertainty present in the solid waste system. Secondly, a series of grey integer submodels construct payoff matrices for a zero-sum two-person game. The ensuing game theoretic analysis is critical for evaluating optimal pricing strategies for tipping fees available to the most significant regional landfills (e.g. Browning-Ferris Industries (BFI) and City of Edinburg) as they compete over disposal contracts. The BFI landfill intrinsically benefits from its competitive pricing policy and central location to solid waste generators. The City of Edinburg landfill, on the other hand, wishes to secure its lucrative solid waste management revenue. It desires a gaming strategy backed by optimality that integrates ambiguity in solid waste generation, design capacity boundaries, and unitary shipping costs. Results show that a two-tiered analysis via grey integer programming-based games may pave the way for 'grey Nash equilibria' pricing tactics that will help the Edinburg landfill maintain its waste contracts.
机译：南德克萨斯州的下里奥格兰德河谷（LRGV）地区成为中美洲和美国之间的仓库和运输中心，并因《北美自由贸易协定》（NAFTA）而对经济产生积极的影响。在10年的时间里，人口增长39.8％，导致该地区人均固体废物处置率提高了25％。垃圾填埋场空间不足，促使垃圾填埋场运营商需要了解在这个竞争激烈的市场中的最佳管理策略。最初，最佳固废模式分配的战略计划将城市的净成本降至最低。这是通过灰色整数编程算法完成的，该算法封装了固体废物系统中存在的所有不确定性。其次，一系列灰色整数子模型构造零和两人博弈的支付矩阵。随后进行的博弈论分析对于评估最佳定价策略至关重要，因为这些定价策略可为最重要的区域垃圾填埋场（例如Browning-Ferris Industries（BFI）和爱丁堡市）提供小费，因为他们在竞争处置合同方面的竞争。 BFI垃圾填埋场从其竞争性价格政策和固体废物产生者的集中位置中受益匪浅。另一方面，爱丁堡市垃圾填埋场希望获得可观的固体废物管理收入。它希望有一种以最优性为后盾的博弈策略，该最优性要在固体废物产生，设计能力边界和统一运输成本中整合模糊性。结果表明，通过基于灰色整数编程的游戏进行的两层分析可能为“灰色纳什均衡”定价策略铺平道路，这将帮助爱丁堡垃圾填埋场维持其废物合同。

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