Multi-objective non-linear programming problem with rough interval parameters: an application in municipal solid waste management

IF 5 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Complex & Intelligent Systems Pub Date : 2024-01-09 DOI:10.1007/s40747-023-01305-y
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Abstract

In dealing with the real-world optimization problems, a decision-maker has to frequently face the ambiguity and hesitancy due to various uncontrollable circumstances. Rough set theory has emerged as an indispensable tool for representing this ambiguity because of its characteristic of incorporating agreement and understanding of all the involved specialists and producing more realistic conclusions. This paper studies an application of the rough set theory for a multi-objective non-linear programming problem that originates for the management of solid wastes. Municipal solid waste management is a global problem that affects every country. Because of the poor waste management system in many nations, the bulk of municipal solid waste is disposed of in open landfills with no recovery mechanism. Hence, an effective and long term waste management strategy is the demand of the day. This research offers an incinerating, composting, recycling, and disposing system for the long-term management of the municipal solid waste. A model for the municipal solid waste management with the goal of minimizing the cost of waste transportation, cost of waste treatment and maximizing the revenue generated from various treatment facilities is developed under rough interval environment. To tackle the conflicting nature of different objectives, an approach is proposed that gives the optimistic and pessimistic views of the decision-maker for optimizing the proposed model. Also, the biasness/preference of the decision-maker for a specific objective is handled by establishing the respective non-linear membership and non-membership functions instead of the linear ones. Finally, to demonstrates the practicality of the proposed methodology, a case study is solved and the obtained Pareto-optimal solution has been compared to those obtained by the existing approaches.

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具有粗略区间参数的多目标非线性编程问题:在城市固体废物管理中的应用
摘要 在处理现实世界的优化问题时,决策者不得不经常面对由于各种不可控因素造成的模糊性和犹豫不决。粗糙集理论因其兼顾所有相关专家的一致意见和理解,并能得出更切合实际的结论的特点,已成为表示这种模糊性不可或缺的工具。本文研究了粗糙集理论在多目标非线性编程问题中的应用,该问题源于固体废物管理。城市固体废物管理是一个全球性问题,影响着每一个国家。由于许多国家的废物管理系统不完善,大部分城市固体废物被露天填埋,没有回收机制。因此,有效和长期的废物管理策略是当务之急。这项研究为城市固体废物的长期管理提供了一个焚烧、堆肥、回收和处置系统。在粗略的区间环境下,开发了一种城市固体废物管理模式,其目标是使废物运输成本、废物处理成本最小化,并使各种处理设施产生的收入最大化。为解决不同目标之间的冲突,提出了一种方法,即给出决策者的乐观和悲观观点,以优化所提出的模型。此外,通过建立各自的非线性成员和非成员函数,而不是线性函数,来处理决策者对特定目标的偏见/偏好。最后,为了证明所提方法的实用性,我们解决了一个案例研究,并将所获得的帕累托最优解与现有方法所获得的帕累托最优解进行了比较。
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来源期刊
Complex & Intelligent Systems
Complex & Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
9.60
自引率
10.30%
发文量
297
期刊介绍: Complex & Intelligent Systems aims to provide a forum for presenting and discussing novel approaches, tools and techniques meant for attaining a cross-fertilization between the broad fields of complex systems, computational simulation, and intelligent analytics and visualization. The transdisciplinary research that the journal focuses on will expand the boundaries of our understanding by investigating the principles and processes that underlie many of the most profound problems facing society today.
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