Optimizing construction project scheduling has received a considerable amount of attention over the past 20 years. As a result, a plethora of methods and algorithms have been developed to address specific scenarios or problems. A review of the methods and algorithms that have been developed to examine the area of construction schedule optimization (CSO) is undertaken. The developed algorithms for solving the CSO problem can be classified into three methods: mathematical, heuristic and metaheuristic. The application of these methods to various scheduling problems is discussed and implications for future research are identified.

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Governments in Australia place great emphasis on the development and expansion of their rail networks to improve productivity and service the increasing needs and demands from businesses and commuters. A case study approach is used to analyze the cost performance of 16 rail projects constructed by a contractor between 2011 and 2014, which ranged from AU$3.4 to AU$353 million. Findings indicate that scope changes during construction were the key contributors that lead to the amendment of each project's original contractual value. As a result, there is a need for public and private sector asset owners to establish a cost contingency using a probabilistic rather than a deterministic approach to accommodate the potential for scope changes during construction. To improve cost certainty during the construction of rail projects, it is suggested that use of collaborative forms of procurement juxtaposed with the use of Building Information Modelling and Systems Information Modelling are implemented. The utilization of such technological and process innovations can provide public and private sector asset owners charged with delivering and maintaining their rail networks with confidence projects can be delivered within budget and are resilient to unexpected events and adaptable to changing needs, uses or capacities.

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