Portfolio optimization is an activity for balancing return and risk. In this paper, we used mean-variance (M-V) portfolio models with buy-in threshold cardinality constraints. This model can be formulated as a mixed integer nonlinear programming (MINLP) problem. To solve constrained problem, propose the use of modified spiral algorithm (SOA). Then, Bartholomew-Biggs Kane’s data to validate our ...

This paper provides a survey of recent progress and software for solving convex mixed integer nonlinear programs (MINLP)s, where the objective and constraints are defined by convex functions and integrality restrictions are imposed on a subset of the decision variables. Convex MINLPs have received sustained attention in recent years. By exploiting analogies to well-known techniques for solving ...

In this work, disjunctive-genetic programming (D-GP), based on the integration of genetic algorithm (GA) with the disjunctive formulations of generalized disjunctive programming (GDP) for the optimization of process networks, has been proposed. Discrete optimization problems, which give rise to the conditional modeling of equations through representations as logic based disjunctions, are very i...

In his 1963 PhD thesis, Wilson proposed the first sequential quadratic programming (SQP) method for the solution of constrained nonlinear optimization problems. In the intervening 48 years, SQP methods have evolved into a powerful and effective class of methods for a wide range of optimization problems. We review some of the most prominent developments in SQP methods since 1963 and discuss the ...

This paper investigates a multi-period rectilinear distance 1-center location problem considering a lineshaped barrier, in which the starting point of the barrier follows the uniform distribution function. In addition, the existing points are sensitive to demands and locations. The purpose of the presented model is to minimize the maximum barrier distance from the new facility to the existing f...

This research studies the single-stage supply chain system operated under JIT technique. A kanban mechanism is employed to assist in linking the production processes in a supply chain system. The number of kanbans, batch size, and the number of batches are determined optimally. Based on this information, kanban operation between two adjacent plants can be worked out for controlling the supply c...

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...

This paper presents a novel, multi-objective mixed-integer nonlinear programming (MINLP) model for a cell formation problem (CFP) with alternative means. Due to existing contradiction among objectives, three are considered: 1) Minimizing the total cost consisting of; intercellular movements, purchasing, operation, and maintenance; 2) maximizing the utilization of machines in the system; 3) mini...

Adaptive Random Searches (ARS) are simple and effective optimization methods used for handling complicated nonconvex / multimodal nonlinear programming (NLP) and mixed-integer nonlinear programming (MINLP) problems. ARS iteratively adapt search characteristics according to the past successful / failure steps. Periodic search domain expansions and contractions improve significantly the reliabili...

This contribution presents a numerical evaluation of the impact of parallelization on the performance of an evolutionary algorithm for mixed-integer nonlinear programming (MINLP). On a set of 200 MINLP benchmarks the performance of the MIDACO solver is assessed with gradually increasing parallelization factor from one to three hundred. The results demonstrate that the efficiency of the algorith...