As a collective and highly dynamic social group, the human crowd is a fascinating phenomenon that has been frequently studied by experts from various areas. Recently, computer-based modeling and simulation technologies have emerged to support investigation of the dynamics of crowds, such as a crowd's behaviors under normal and emergent situations. This article assesses the major existing technologies for crowd modeling and simulation. We first propose a two-dimensional categorization mechanism to classify existing work depending on the size of crowds and the time-scale of the crowd phenomena of interest. Four evaluation criteria have also been introduced to evaluate existing crowd simulation systems from the point of view of both a modeler and an end-user. We have discussed some influential existing work in crowd modeling and simulation regarding their major features, performance as well as the technologies used in this work. We have also discussed some open problems in the area. This article will provide the researchers with useful information and insights on the state of the art of the technologies in crowd modeling and simulation as well as future research directions.

In the face of globalization and rapidly shrinking product life cycle, manufacturing companies are trying different means to improve productivity through management of machine utilization and product cycle-time. Job shop scheduling is an important task for manufacturing industry in terms of improving machine utilization and reducing cycle-time. However, job shop scheduling is inherently a NP-hard problem with no easy solution. This paper describes a novel approach that uses the honey bees foraging model to solve the job shop scheduling problem. Experimental results comparing the proposed honey bee colony approach with existing approaches such as ant colony and tabu search are presented

A bee colony optimization (BCO) algorithm for traveling salesman problem (TSP) is presented in this paper. The BCO model is constructed algorithmically based on the collective intelligence shown in bee foraging behaviour. Experimental results comparing the proposed BCO model with some existing approaches on a set of benchmark problems are presented.