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GENERAL LINEAR PROGRAMMING NOTATION  71



                        MANAGEMENT SCIENCE IN ACTION



                        Using Linear Programming for Traffic Control
                           he Hanshin Expressway was the first urban toll  In the first phase of the steady-state case, the
                        T expressway in Osaka, Japan. Although in 1964  Hanshin system uses a linear programming model
                        its length was only 2.3 kilometres, today it is a large-  to maximize the total number of vehicles entering the
                        scale urban expressway network of 200 kilometres.  system, while preventing traffic congestion and
                        The Hanshin Expressway provides service for the  adverse effects on surrounding road networks. The
                        Hanshin (Osaka-Kobe) area, the second-most popu-  data that drive the linear programming model are
                        lated area in Japan. An average of 828 000 vehicles  collected from detectors installed every 500 metres
                        use the expressway each day, with daily traffic some-  along the expressway and at all entrance and exit
                        times exceeding one million vehicles. In 1990, the  ramps. Every five minutes the real-time data col-
                        Hanshin Expressway Public Corporation started using  lected from the detectors are used to update the
                        an automated traffic control system in order to max-  model coefficients, and a new linear programme
                        imize the number of vehicles flowing into the express-  computes the maximum number of vehicles the
                        way network.                                expressway can accommodate.
                          The automated traffic control system relies on two  The automated traffic control system has been
                        control methods: (1) limiting the number of cars that  successful. According to surveys, traffic control
                        enter the expressway at each entrance ramp; and (2)  decreased the length of congested portions of
                        providing drivers with up-to-date and accurate traffic  the expressway by 30 per cent and the duration
                        information, including expected travel times and infor-  by 20 per cent. It proved to be extremely cost
                        mation about accidents. The approach used to limit  effective, and drivers consider it an indispensable
                        the number of vehicles depends upon whether the  service.
                        expressway is in a normal or steady state of opera-
                                                                    Based on T. Yoshino, T. Sasaki and T. Hasegawa, ‘The Traffic-Control
                        tion, or whether some type of unusual event, such as  System on the Hanshin Expressway’ Interfaces (January/February
                        an accident or a breakdown, has occurred.   1995): 94–108.




                                         The Management Science in Action, Using Linear Programming for Traffic Control,
                                      provides just one of many examples of the widespread use of linear programming. In the
                                      next two chapters we will see many more applications of linear programming.


                       Problems


                                   1 Which of the following mathematical relationships could be found in a linear programming
                                      model, and which could not? For the relationships that are unacceptable for linear
                                      programmes, state why.
                                      a.  1x 1 +2x 2   1x 3   70
                                      b. 2x 1   2x 3 ¼ 50
                                               2
                                      c. 1x 1   2x 2 +4x 3   10
                                        p ffiffiffiffiffi
                                      d.  3  x 1 +2x 2   1x 3   15
                                      e. 1x 1 +1x 2 +1x 3 ¼ 6
                                      f. 2x 1 +5x 2 +1x 1 x 2   25
                                   2 Find the feasible solution points for the following constraints:
                                      a. 4x 1 +2x 2   16
                                      b. 4x 1 +2x 2   16
                                      c. 4x 1 +2x 2 ¼ 16




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