The study of the entrepreneurial mindset has provided valuable insights into the cognitive strategies that impact entrepreneurial activities. Researchers have identified several biases and heuristics employed by entrepreneurs, which significantly influence their decision-making processes and...

Over the past decades psychological theories have made significant headway into economics, culminating in the 2002 (partially) and 2017 Nobel prizes awarded for work in the field of Behavioural Economics. Many of the insights imported from psychology into economics share a common trait: the...

Background: Order picking is a critical activity in end-product warehouses, particularly using the picker-to-part system, entail substantial manual labor, representing approximately 60% of warehouse work. Methods: This study develops a new linear model to perform batching, which allows for...

This paper is devoted to the development of heuristics for the dynamic pricing problem. A discrete time model of dynamic pricing on the fixed time horizon is proposed. It is applicable to products that satisfy two properties: 1) product value expires at a certain predetermined date, and 2)...

This paper provides an overview of behaviors and learning of heterogeneous economic agents -whether individuals or firms- within complex evolving economies. It aims to explore the microfoundation of agency and learning, two fundamental aspects that constitutively contribute to the emergence of...

Purpose - The Purpose of this study is to investigate the impact of behavioral biases on investment decisions through a serial mediation of overconfidence and disposition effects. Design/methodology/approach The authors assess the behavioral biases affecting the investment decisions of life...

This paper investigates a Multi-Stage Stochastic Districting Problem (MSSDP). The goal is to devise a districting plan (i.e., clusters of Territorial Units—TUs) accounting for uncertain parameters changing over a discrete multi-period planning horizon. The problem is cast as a multi-stage...

This paper provides an overview of behaviors and learning of heterogeneous economic agents -whether individuals or firms- within complex evolving economies. It aims to explore the microfoundation of agency and learning, two fundamental aspects that constitutively contribute to the emergence of...

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...

This study presents a supply chain model for optimizing milk collection routing in multi-depot networks. The problem consists of a fleet of vehicles that leaves their depots (i.e., typically the driver's houses), visits an assigned set of farms to collect the raw milk, and delivers it to the...