Simulation is required for the verification of models for elements, systems, and processes of the existing real world, as well as aspects of a targeted future world. It facilitates development of concepts and experiments in a virtual world. Experimentation in a virtual world reduces costs, identifies and mitigates risks, and enhances gains for future designs. The varied arena of needs and situations for simulation has instigated development of varied frameworks and techniques for simulation. This is the second volume of a two-part collection of articles authored by various authors on simulation studies, techniques, and applications. The editors have divided the volume into two parts.

Part 1 focuses on tools and techniques and has three chapters, each focusing on one aspect of simulation and related modeling illustrated by a case study. The first chapter, by Jennie Lioris and colleagues, discusses the role of conceptual frameworks with a case study of complex traffic flow problems using data from the Los Angeles metro area. The suggested framework includes traffic response signal modeling, an adaptive/pre-timed control algorithm, max-pressure practical policy, discrete event simulation, performance evaluation, and queueing network modeling. The second chapter focuses on simulation for a complex network analysis framework and uses the Mexico City Public Transport System as a case study. The analytical framework consists of modeling urban mobility, decision support for traffic flow optimization, traffic flow simulation, and synthetic analysis. The third chapter, by Kibira and Shao, discusses techniques for using data mining and simulation for optimal decision making with a case study from auto parts manufacturing with minimum energy consumption and production time. Topics discussed are data mining techniques, including those for association rule mining and clustering, discovering rules for auto part manufacturing, simulation optimization problems, and formulating integrated data mining.

Part 2 has six chapters, and each discusses a case study on simulation optimization. The first chapter, by Mota and colleagues, discusses simulation for improving airport performance with modeling and optimization techniques, using data from the Netherlands’ air network. In previous works, experimental design methodologies for modeling and analyzing airport systems such as runway systems, taxiway systems, approach/depart routes, and airspace have been discussed. The second chapter, by Rodiac and Baggia, deals with airport ground crew scheduling using heuristics and scheduling. The discussion hovers around systems dynamics, discrete event simulation and agent-based modeling to develop a heuristic algorithm, and models and simulation of aircraft traffic and ground operations. The third chapter is on the optimization of runway sequences for airports under a collaborative decision-making (CDM) regime. It explores the CDM concept, operations parameters, heuristic algorithms, and system simulation. The chapter by Becerra and Alvarez-Icaza is on simulation and optimization for power flow in hybrid-electric vehicles (HEV). Using Matlab/Simulink the authors give an overview of HEV and mathematical models for HEV power flows, optimization problems, and simulation. The next chapter, by Evans, DePuy, and Gupta, describes an analysis of retail ordering policies incorporating minimum purchases from a vendor using simulation and optimization tools. It discusses facets of inventory and distribution policies, as well as the simulation and optimization of retail operations. The last chapter, by Wellens and colleagues, discusses the optimization and simulation of fuel distribution operations using data from Mexico City. The optimization problem has been formulated using cost variables for ordering, transport, and distribution, subject to network topology.

Each chapter has a comprehensive list of references, a discussion on status, and suggestions for future work. In general, all chapters are easy to read. This collection would be of interest to industrial operations analysts and researchers in industrial process simulation.