Reverse logistics, induced by various forms of return, has received growing attention
throughout this decade. Reverse logistics network design is a major strategic issue. This …

Most real world search and optimization problems naturally involve multiple responses. In
this paper we investigate a multiple response problem within desirability function framework …

With the change in global climate and environment, the prevalence of extreme rainstorms
and flood disasters has increased, causing serious economic and property losses …

Cloud workloads are highly dynamic and complex, making task scheduling in cloud
computing a challenging problem. While several scheduling algorithms have been …

In the context of global climate change and the continuous development of urban areas,
rainfall-inundation modeling is a common approach that provides critical support for the …

Computer simulation is a powerful evaluative tool for the design and configuration of
stochastic systems. Methodologies are needed that assist simulation end users in locating …

This paper presents an improved genetic algorithm approach, based on new ranking
strategy, to conduct multiobjective optimization of simulation modeling problems. This …

Simulation optimization is an approach that is used to solve problems involving stochastic
components. This paper presents a Lexicographic Nelder–Mead (LNM) based simulation …

This paper proposes a simulated annealing variant for optimization problems in which the
solution quality can only be estimated by sampling from a random distribution. The aim is to …

Hybrid approach in a production line for multi-objective simulation optimization Page 1 Journal
of the Faculty of Engineering and Architecture of Gazi University 34:4 (2019) 1847-1859 Hybrid …