A Bi-level Multiobective Optimization Model for Risk Management to Utilize Wastes in Stone Industry under Fuzzy Environment

  • Abid Hussain Nadeem
  • Muhammad Hashim
  • Muhammad Nazim
Conference paper

DOI: 10.1007/978-1-4471-4600-1_34

Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 185)
Cite this paper as:
Nadeem A.H., Hashim M., Nazim M. (2013) A Bi-level Multiobective Optimization Model for Risk Management to Utilize Wastes in Stone Industry under Fuzzy Environment. In: Xu J., Yasinzai M., Lev B. (eds) Proceedings of the Sixth International Conference on Management Science and Engineering Management. Lecture Notes in Electrical Engineering, vol 185. Springer, London

Abstract

Control and management of waste materials created during stone production is one of the most important problems of stone industry and modern societies today. Waste materials which are different depending on properties of structure and construction technique generally consist of materials such as concrete, brick, stone, briquette, wood, metal, glass, gypsum, plastic, ceramic [1]. This paper is about how to optimize the stone industry. The plant considered as the leader level will make a strategy to utilize the wastes amount for waste department. The waste department considered as the follower level will make a decision to produce different stone products under the utilizing constraint. Due to the lack of historical data, some emission coefficients are considered as fuzzy numbers.Therefore, a bi-level multiobjective optimization model with possibilistic constraints are developed to get the maximum profit and control the pollution. At the end, a case study is proposed to show the efficiency of the proposed model.

Keywords

Bi-level multi-objective programming Possibilistic constraint Waste utilization in stone industry Fuzzy simulation 

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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Abid Hussain Nadeem
    • 1
  • Muhammad Hashim
    • 1
  • Muhammad Nazim
    • 1
  1. 1.Uncertainty Decision-Making LaboratorySichuan UniversityChengduP. R. China

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