At the strategic level, closed-loop supply chain (CLSC) management involves long-term decisions regarding the location and capacity allocation of forward/reverse logistics facilities, the assignment of products to facilities, and the distribution of products between facilities and their end users or suppliers. Both demand and return handling must be taken into account, and the overall problem b...

Based on environmental, legal, social, and economic factors, reverse logistics and closed-loop supply chain issues have attracted attention among both academia and practitioners. This attention is evident by the vast number of publications in scientific journals which have been published in recent years. Hence, a comprehensive literature review of recent and state-of-the-art papers is vital to ...

The Industrial Ecology (IE) is a new interdisciplinary field focused on sustainable development. IE aims to the shifting of industrial processes from open-loop systems where different resources move through a system to become wastes to a closed-loop system where wastes become inputs for new processes. This paper introduces a Green Virtual Enterprise (GVE) model as an emerging sustainable manufa...

The concern about customer satisfaction and transportation cost in the business environment has spurred an interest in designing a flexible logistics network. This paper proposes a multi-delivery path closed-loop supply chain network to find not only the most cost efficient network design but also the best path to deliver the products to customers. To tackle with such an NP-hard problem an Arti...

Research on semantics in Genetic Programming (GP) has increased dramatically over the last number of years. Results in this area clearly indicate that its use in GP can considerably increase GP performance. Motivated by these results, this paper investigates for the first time the use of Semantics in Muti-Objective GP within the well-known NSGA-II algorithm. To this end, we propose two forms of...

In this paper, a GPGPU (general purpose graphics processing unit) compatible Archived based Stochastic Ranking Evolutionary Algorithm (G-ASREA) is proposed, that ranks the population with respect to an archive of non-dominated solutions. It reduces the complexity of the deterministic ranking operator from O(mn) to O(man) and further speeds up ranking on GPU. Experiments compare G-ASREA with a C...

Obtaining a well distributed non-dominated Pareto front is one of the key issues in multi-objective optimization algorithms. This paper proposes a new variant for the elitist selection operator to the NSGA-II algorithm, which promotes well distributed non-dominated fronts. The basic idea is to replace the crowding distance method by a maximin technique. The proposed technique is deployed in wel...

An improved harmony search algorithm for constrained multi-objective optimization problems is proposed in this paper. Inspired by Particle Swarm Optimization, an inductor particle is introduced to speed up the convergence rate of the CMOHS. Two populations are adopted to increase the opportunity of finding the optimal solutions. Numerical experiments are divided into two parts: the first one co...

This paper presents NSGA-PINN, a multi-objective optimization framework for the effective training of physics-informed neural networks (PINNs). The proposed uses non-dominated sorting genetic algorithm (NSGA-II) to enable traditional stochastic gradient algorithms (e.g., ADAM) escape local minima effectively. Additionally, NSGA-II enables satisfying initial and boundary conditions encoded into ...

The article describes the ways of industrial development in era transition from a linear model economy to circular model, as well new trends logistics. It shows interconnection processes production systems, logistics and services, their role ensuring sustainable green growth. is shown that by closing loop product lifecycles, reverse plays an important transitioning economy. presents example pla...