Highway work zones create potential risks for both traffic and workers in addition to traffic congestion and delays that result in increased road user delay, traffic crashes, and vehicle emissions. The Federal Highway Administration (FHWA) and state departments of transportation (DOTs) are continuously seeking to improve work zone safety and mobility. To accomplish this, the layout of highway work zones needs to be carefully planned and optimized to accomplish the multiple and often conflicting objectives of maximizing safety and mobility. This article presents the development of an innovative multiobjective optimization model to search for and identify a set of Pareto-optimal work zone layouts that provide a wide range of optimal trade-offs between minimizing traffic delays and minimizing the probability of crashes. The model has four phases: (1) identify all relevant decision variables for work zone layout, (2) formulate the optimization objective functions in the model, (3) define all relevant and practical constraints that affect the optimization problem, and (4) perform the model-optimization computations using multiobjective genetic algorithms. The performance of the developed optimization model was analyzed and verified using an application example of work zone layout. The results of the analysis of this example illustrate the novel and unique capabilities of the developed model in searching for and identifying optimal work zone layouts. These new and unique capabilities are expected to support state DOTs and construction planners in their ongoing efforts to maximize work zone safety and reduce traffic delays in the work zone area.