Background: The Vehicle Routing Problem with Time Windows (VRPTW) has been extensively researched due to its applicability across various real-world domains, including logistics, healthcare, and distribution systems. With the global elderly population projected to continue increasing, the demand...

Optimizing solid waste management (SWM) is essential for ensuring a sustainable and healthy environment in a city. This study considers a two-echelon solid waste logistics system (2E-SWLS) in a metropolitan city with a fleet of capacitated heterogeneous vehicles. The problem consists of waste...

This research focuses on modeling and solving a bi-objective hybrid flow shop scheduling problem, considering uncertain job-dependent setup times and worker constraints. The main objective of the mathematical model is to simultaneously minimize the Maximum Completion Time (Cmax) and minimize the...

This work looks for the optimal allocation of different assets, namely, the G7 stock indices, commodities (gold and WTI crude oil), cryptocurrencies (Bitcoin and Ripple), and S&P Green Bond, over four periods: before the COVID-19 crisis, during the COVID-19 crisis and before the Russia-Ukraine...

Background: Urban rail transit ensures efficient mobility in densely populated metropolitan areas. This study focuses on the Cairo Metro Network and addresses the Rolling Stock Rotation Planning Problem (RSRPP), aiming to improve operational efficiency and service quality. Methods: A...

Background: Managing multiproduct pipeline systems is a complex task of critical importance in the petroleum industry. Experts frequently rely on simulation tools to design and validate pumping operation schedules. However, existing tools are often problem-specific and too slow to be effectively...

The continuous annealing of flat steel improves its properties for applications such as automotive manufacturing. Scheduling these processes on Parallel Heterogeneous Annealing Lines (PHALs) is complex due to diverse coil properties, incompatible process modes, and due date constraints....

The Dwarf Mongoose Optimization (DMO) algorithm, inspired by the behaviors and foraging patterns of dwarf mongooses, is a recently formulated swarm-based metaheuristic method emulating the cooperative behavior of mongooses during food searches. The DMO algorithm effectively addresses various...

This study presents a comprehensive approach to managing pharmaceutical inventory during pandemics. The study focuses on optimizing investment strategies for promoting COVID-19 medicine across various price ranges while carefully preserving pharmaceutical products. We develop a customized...

Metaheuristics are widely used to address complex optimisation problems where traditional exact methods are computationally infeasible or insufficiently flexible. With the rapid advancement of artificial intelligence, large language models, such as ChatGPT, Claude, Gemini, and LLaMA, have...

This is a slightly revised version of the purposely provocative keynote presented at the FDR library for the Levy Institute Summer Seminar on Money, Finance, and Public Policy. References have been added.

Background: Logistics and transport, core of many business processes, are continuously optimized to improve efficiency and market competitiveness. The paper describes a modular coordination of vehicle routing and bin packing problems that enables independent instances of the problems to be...