The present study attempts to deal with two problems: optimal allocation of distribution generations (DGs) and reconfiguration a system satisfy several multiobjectives including smoothing the voltage profile, minimizing cost reliability, balancing amount load on end-user side. These problems are merged into one single optimization problem aforementioned objective functions. type is mixed-intege...

In this paper we propose a novel continuous time model based on state task network for the problem of scheduling m products in n continuous processing units with simultaneous arrival of liquid inputs and multiple intermediate upliftment dates. The units can process only one product line at a time and are buffered by fixed capacity storage tanks. An optimization model for the problem tries to ba...

This work is concerned with the efficient design of a reverse logistics network using an extended version of models currently found in the literature. Those traditional, basic models are formulated as mixed integer linear programs (MILP-model) and determine which facilities to open that minimize the investment, processing, transportation, disposal and penalty costs while supply, demand and capa...

We propose a bilevel mixed-integer nonlinear programming (MINLP) model for the optimal investment of biorefinery facilities considering non-cooperative farmers and biofuel consumers. Interactions among the supply chain players are captured through a single-leader-multiple-follower Stackelberg game under the generalized Nash equilibrium assumption. Given a three-echelon superstructure, the lead ...

This paper studies the integration of geological sequestration and microalgae biofixation options for greenhouse gas (GHG) abatement using a supply chain optimisation approach. We propose a multi-scale multi-period mixed-integer nonlinear programming (MINLP) model, which accounts for CO2 transportation pipeline network design, algae processing route and product selection, as well as the seasona...

A mixed-integer nonlinear programming problem (MINLP) is a problem with continuous and integer variables and at least, one nonlinear function. This kind of problem appears in a wide range of real applications and is very difficult to solve. The difficulties are due to the nonlinearities of the functions in the problem and the integrality restrictions on some variables. When they are nonconvex t...

We consider strategies for integrated design and control through the robust and efficient solution of a mixed-integer dynamic optimization MIDO) problem. The algorithm is based on the transformation of the MIDO problem into a mixed-integer nonlinear programming (MINLP) rogram. In this approach, both the manipulated and controlled variables are discretized using a simultaneous dynamic optimizati...

Numerical algorithm developers need standardized test instances for empirical studies and proofs of concept. There are several libraries available for finitedimensional optimization, such as the netlib or the miplib. However, for mixed-integer optimal control problems (MIOCP) this is not yet the case. One explanation for this is the fact that no dominant standard format has been established yet...

in this paper, the energy efficient resource allocation in noma-based heterogeneous cellular network(hcn) systems is investigated. since energy consumption and its limitations is one of the important challenges in fifth generation of cellular networks (5g), we propose a resource allocation problem which allocates power and subcarriers to multiple users to achieve the best system energy efficien...

An improved outer-approximation algorithm for MINLP optimization is proposed in this paper which is aimed at the solution of problems where convexity conditions may not hold. The proposed algorithm starts by solving the NLP relaxation. If an integer solution is not found, a sequence of iterations consisting of NLP subproblems and MILP master problems is solved. The proposed MILP master problem ...