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The railroad blocking problem (RBP) is an important decision for freight railroad companies. The objective of this problem is to minimize the costs of delivering all commodities by deciding which interyard blocks to build and specifying the assignment of commodities to these blocks. In this paper, a mathematical model is presented for the RBP on Iran Railways. Its decision variables identify blocking scheme and demand assignment to these blocks. The RBP in medium and large sizes is not solvable with any commercial software available in the market. Therefore, a solution method based on tabu search algorithm is proposed for the suggested model. For evaluating the proposed algorithm, several simulated test problems are randomly generated and solved. The obtained results on the test problems are compared with those of solutions generated by CPLEX software. The comparison shows high efficiency and effectiveness of the proposed algorithm. The proposed model and solution method are applied to build a blocking plan for the Iranian railway. [ABSTRACT FROM AUTHOR]

Seasonal demand variation is a somewhat neglected aspect of transit demand. Many cities worldwide experience seasonal variation of passenger demand that deserves not only changes of service frequency, but also and often more importantly, changes in the transit network of routes. Literature dealing with optimal bus networks shows that it is an non polynomial (NP)-hard complexity problem with the demand being the most important variable affecting the network. Thus, the bus network of concern should be robust from the optimization perspective when a new demand arises. This paper introduces a model and a solution algorithm to take into account the variation of passenger demand in the design of bus networks. The solution algorithm developed is a hybrid method that optimizes the design of a bus network at the route and network levels. The model was applied to the city of Mashhad in Iran with a population of over 3.2 million and 20 million visitors annually. The results are promising and demonstrate how to determine the best single network of bus routes to suit variable passenger demand. [ABSTRACT FROM AUTHOR]