This work evaluates the performance of salp swarm algorithm (SSA) for truss system optimization problems and presents a novel method called modified (MSSA). Five structures, previously optimized by metaheuristics containing discrete continuous variables, were used evaluations. Size size–shape types considered. Although SSA performs poorly has convergence issues in initial random solutions, it r...

In this paper, we extend a bio-inspired algorithm called the porcellio scaber algorithm (PSA) to solve constrained optimization problems, including a constrained mixed discrete-continuous nonlinear optimization problem. Our extensive experiment results based on benchmark optimization problems show that the PSA has a better performance than many existing methods or algorithms. The results indica...

In the literature, thermal insulation systems with a fixed number of heat intercepts have been optimized with respect to intercept locations and temperatures. The number of intercepts and the types of insulators that surround them were chosen by parametric studies. This was because the optimization methods used could not treat such categorical variables. Discrete optimization variables are cate...

This study addresses the traffic light scheduling problem for pedestrian–vehicle mixed-flow networks. A macroscopic model, which strikes an appropriate balance between pedestrians’ needs and vehicle drivers’ needs, is employed to describe in a framework. The objective of this minimize total network-wise delay time vehicles pedestrians within given finite-time window, crucial avoid congestion ur...

This paper presents the development of a mixed-variable optimization framework for the aeroelastic analysis and design of active twist rotors. Proper tailoring of the blade properties can lead to the maximization of the active twist and the control authority for vibration reduction under operating conditions. Thus, using mathematical optimization, the crosssectional layout is designed using con...

Optimization as an enabling technology has been one of the big success stories in process systems engineering. In this paper we present a review on recent research work in the area of logic-based discrete/continuous optimization. In particular, recent advances are presented in the modeling and solution of nonlinear mixed-integer and generalized disjunctive programming, global optimization and c...

In this paper we present an extension of ant colony optimization (ACO) to continuous domains. We show how ACO, which was initially developed to be a metaheuristic for combinatorial optimization, can be adapted to continuous optimization without any major conceptual change to its structure. We present the general idea, implementation, and results obtained. We compare the results with those repor...

This study deals with performance-based design optimization (PBDO) of steel moment frames employing four different metaheuristics consisting of genetic algorithm (GA), ant colony optimization (ACO), harmony search (HS), and particle swarm optimization (PSO). In order to evaluate the seismic capacity of the structures, nonlinear pushover analysis is conducted (PBDO). This method is an iterative ...

Engineering design problems often involve nonlinear criterion functions, including inequality and equality constraints, and a mixture of discrete and continuous design variables. Optimization approaches entail substantial challenges when solving such an all-inclusive design problem. In this paper, a modification of the Particle Swarm Optimization (PSO) algorithm is presented, which can adequate...