OPTIMUM CONSTRUCTION EQUIPMENT FLEETS FOR ROAD SURFACE OPERATIONS

Abstract

Poor subgrade soil condition which is very sensitive to moisture presents a construction challenge for all pavement engineers. One of the case histories which became a dilemma for the Azadegan freeway in Tehran is the presence of waste material in subgrade soil. This paper discusses the site investigation to gather some useful information about the principal causes of these problems and deals with some in-depth Laboratory tests which have been done in the soil and asphalt laboratory of Tehran municipality. The pavement condition index known as PCI has been calculated to address all the deteriorations and causes to make a good decision. After analyzing all the gathered data, several methods has been discussed, for example, deep mixing, short concrete piles, shredded tires, and injection. Finally based on the lack of facilities and budget shortage, a retaining wall with geogrids has been chosen for this very special case which is right now under traffic flow. The optimum selection of equipment fleets in surface work operations is a key element to the success of any road construction project. For years, computer simulations have been used to predict the performance of construction operations based on process flows and resources utilized. However, simulations in essence are not a resource optimization platform, since all possible resource combinations should be examined within the simulation process itself. This paper proposes a hybrid mechanism that integrates discrete event simulation and genetic algorithms to efficiently determine the best resource combination for the surface work operations in road construction. The paper employs genetic algorithms (GAs) for minimizing the total cost of surface work operations examined. A dynamic link utilizes a simulation engine, which models a road’s surface work operations, to calculate the fitness of the generated chromosomes. An actual case study is further utilized to illustrate the effectiveness and performance of this hybrid mechanism.