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traffic accidents. HAZMAT transportation has been an active area of research and a large number of literatures relating to HAZMAT in the area of risk management, operation research, and decision making has been available in literatures for last twenty years. Application of proper routing decisions is one of the efficient ways that enables decision makers to achieve safe transportation of HAZMAT, and it is this aspect of HAZMAT transportation that has been focused in this study. The core concept in HAZMAT routing is similar to the one in Vehicle Routing Problem with Time Window (VRPTW), a common application of mathematical programming in business logistics 3) . Risk is the primary term that separates HAZMAT transportation problem from the rest of transportation problems. Moreover, HAZMAT routing is a multiobjective activity involving multiple stakeholders with often conflicting priorities. Beside risk, minimizing travel time is the main objective in any HAZMAT shipment with shipper's point of view. Numbers of HAZMAT transportation studies considering numbers of attributes are available in literatures, most of which focuses on finding shortest paths for a given origin destination pair. However, in reality, HAZMAT transportation problem particularly based on land mode like normal vehicle routing problem calls for the determination of a set of optimal routes to be traveled by a fleet of vehicles thus satisfying the demand and time window constraints of a prespecified number of customers. Owing to this particular VRPTW aspect of HAZMAT shipment, we present a new multiobjective HAZMAT VRPTW model and subsequently a meta heuristic approach to solve this problem. Unlike existing VRPTW studies, route choice and routing processes of transportation here have been carried out as a single step process. The requirement of consideration of multiple objectives during both route choice and routing in HAZMAT shipment calls for their simultaneous consideration for finding optimal set of paths. A metaheuristic solution technique based on Ant Colony Systems (ACS) for solving HAZMAT vehicle routing problem is presented. The proposed algorithm is supplemented by labeling algorithm for processing route choice and routing simultaneously as a single step process. The proposed solution approach is then used to solve a HAZMAT routing problem in a test network consisting of 12 nodes and 34 links. The paretooptimal set obtained provides several nondominated routing options based on varying objectives for decision making process. Alternative application of such solutions not only ensures safe and economic HAZMAT transportation but also helps to minimize accumulation of risk in particular links

MINIMIZING EXPOSURE RISK AND TRAVEL TIMES OF HAZARDOUS MATERIAL TRANSPORTATION IN URBAN AREAS