<![CDATA[The study focuses on the important problem of resource allocation in large, complicated networks of transportation by utilizing goal programming (GP) technique. On the other hand, multi-objective multi-item transport problem is considered under competing objectives such as minimization of transportation costs and reduction in delivery time, environmental impact abatement plus maximization of vehicle utilization. In this paper, such a DSP model is constructed as viewed in its entirety and tightly embedded with a fuzzy goal reaching technique under realistic modifications of transportation circumstances. The model is calibrated using synthetic data from a hypothetical Iraqi road network, and the optimization problem is solved in WinQSP software. Comparison of the final solution indicates that the goal programming outperforms single-objective approaches, showing 18-24% cost reduction with less service level violation and carbon emission. The study is useful for urban logistics planning in the aim of sustainable development, and it also enriches the transport optimization analysis methods for decision maker. This is especially important in emerging countries characterized by limited resources, where “trade-offs” and not just the maximization of some social welfare function play a crucial role for managing transportation systems.]]>
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