Using concave optimization methods for inexact quadratic programming problems with an application to waste management
Sumati Mahajan, Shiv Kumar Gupta, Izhar Ahmad, Suliman S. Al-Homidan
Abstract
Open-access reader
Sumati Mahajan, Shiv Kumar Gupta, Izhar Ahmad, Suliman S. Al-Homidan
Abstract
Open-access reader
Abstract Quadratic programming is potentially capable of strategic decision making in real world problems. However, practical problems rarely conform to crisp parameters, and hence the prospects of these problems with inexact parameters are inevitably higher. The existing studies regarding public welfare schemes/ organizations reveal that their objectives end up as minimization of cost functions and are governed by linear or concave quadratic programming problems. The present study proposes a method that can be applied to concave type quadratic objective function subject to linear constraints with inexact parameters. A comparison is also drawn with existing methods to establish its simplicity and efficiency. Further, a numerical example is illustrated, and finally, a waste management problem is formulated and solved using the proposed method.
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Abstract Quadratic programming is potentially capable of strategic decision making in real world problems. However, practical problems rarely conform to crisp parameters, and hence the prospects of these problems with inexact parameters are inevitably higher. The existing studies regarding public welfare schemes/ organizations reveal that their objectives end up as minimization of cost functions and are governed by linear or concave quadratic programming problems. The present study proposes a method that can be applied to concave type quadratic objective function subject to linear constraints with inexact parameters. A comparison is also drawn with existing methods to establish its simplicity and efficiency. Further, a numerical example is illustrated, and finally, a waste management problem is formulated and solved using the proposed method.
Key concepts: Quadratic programming, Mathematical optimization, Mathematics, Minification, Quadratic equation, Linear programming, Simplicity, Sequential quadratic programming