Experimental evaluation of simulated annealing algorithms for the time–cost trade-off problem

This paper evaluates variants of a simulated annealing algorithm which solve the total cost minimization problem in activity networks in the case that discrete time–cost execution modes are allowed on the project activities. This problem is a special case of the well known discrete time–cost trade-off problem (DTCTP). Based on a sample of randomly generated activity networks, formal tests of statistical significance are utilized to test both the quality of solutions and the time efficiency of algorithms versus problem factors. A procedure issued from the extreme values statistics is also applied on problem instances in order to determine, on the one hand, the confidence interval estimate of the optimum solution for each algorithm and, on the other hand, when to stop the running of an algorithm.