this paper presents a formulation of unit commitment for thermal units integrated with wind and solar energy systems and electrical vehicles with emphasizing on mixed integer nonlinear programming (minlp). the renewable energy resources are included in this model due to their low electricity cost and positive effect on environment. as well as, coordinated charging strategy of electrical vehicle...

The paper examines the applicability of mathematical programming methods to the simultaneous optimization of the structure and the operational parameters of a combined-cycle-based cogeneration plant. The optimization problem is formulated as a non-convex mixed-integer nonlinear problem (MINLP) and solved by the MINLP solver LaGO. The algorithm generates a convex relaxation of the MINLP and appl...

The methods to solve the stochastic MINLP problems fall into two categories: numerical integration method and sample average method. The numerical integration method utilizes numerical integration techniques to calculate the multi-dimensional integrals, such as the Gaussian Quadratures/Cubatures method. The Monte Carlo simulation is one of the most widely used sample average methods. Acevedo an...

Global optimization for sustainable design and synthesis of a large-scale algae processing network under economic and environmental criteria is addressed. An algae processing network superstructure including 7800 processing routes is proposed. Based on the superstructure, a multiobjective mixed-integer nonlinear programming (MINLP) model is developed to simultaneously optimize the unit cost and...

In this paper we address the development of an MINLP optimization model for the synthesis of paraxylene separation processes based on crystallization technology. A superstructure is proposed that considers different alternative designs and operating conditions for the recovery of a high purity paraxylene product from a feed stream containing other xylene isomers and ethylbenzene. The goal is to...

Design, synthesis and scheduling issues are considered simultaneously for multipurpose batch plants. A previously proposed continuous-time formulation for scheduling is extended to incorporate design and synthesis. Processing recipes are represented by the State-Task Network. The superstructure of all possible plant designs is constructed according to the potential availability of all processin...

This paper presents the mixed-integer nonlinear programming (MINLP) optimization model for the nonlinear discrete time–cost trade-off problem (NDTCTP). The nonlinear total project cost objective function of the proposed MINLP optimization model is subjected to a rigorous system of generalized precedence relationship constraints between project activities, project duration constraints, logical c...

A rigorous decomposition-based approach for solution of nonseparable mixedinteger nonlinear programs involving factorable nonconvex functions is presented. The proposed algorithm consists of solving an alternating sequence of Relaxed Master Problems (a Mixed-Integer Linear Program) and nonlinear programming problems. The number of major iterations can be significantly decreased by use of piecew...

We present a specialized branch-and-bound (b&b) algorithm for the Euclidean Steiner tree problem (ESTP) in R and apply it to a convex mixed-integer nonlinear programming (MINLP) formulation of the problem, presented by Fampa and Maculan. The algorithm contains procedures to avoid difficulties observed when applying a b&b algorithm for general MINLP problems to solve the ESTP. Our main emphasis ...

A chance constrained optimization problem over a finite distribution involves a set of scenario constraints from which a small subset can be violated. We consider the setting where all scenario constraints are mixed-integer convex. Existing works typically consider a mixed integer nonlinear programming (MINLP) formulation of this problem by introducing binary variables to indicate which constra...