Simulated annealing for financing cost distribution based project payment scheduling from a joint perspective

Abstract

Based on the distribution of the project financing cost over the contractor and the client, this paper involves the project payment scheduling problem from a joint perspective of the two parties. In the problem, the project financing cost is defined as the expense for raising money from the outside or the opportunity cost of the capital devoted into the project and the objective is to find the project payment schedule that can not only maximize the joint revenue of the two parties but also be accepted by them. Based on the characteristics of the problem, an optimization model consisting of two submodels is constructed using the activity-based method. For the strong NP-hardness of the problem, two simulated annealing algorithms with different searching structures are developed and compared with the multistart iterative improvement method on the basis of a computational experiment performed on a data set generated randomly. The results show that the simulated annealing algorithm with the nested loop module seems to be the most promising algorithm for solving the defined problem especially when the scale of the problem becomes larger. In addition, the influences of some key parameters on the computational results are investigated through the full factorial experiment and a few useful conclusions are drawn. KeywordsProject scheduling • Progress payments • Financing cost distribution • Simulated annealing Z. He ( ) •

Robust Optimization for the Discrete Time-Cost Tradeoff Problem with Cost Uncertainty

“…NPV maximization bears similarity to the payment scheduling problem, where both the activity start times and the cash flows can be chosen by the decision maker Padman 1999, 2001;He et al 2012;Kolisch and Padman 2001). It would be instructive to study the effects of uncertainty and risk aversion in the context of this problem, which to our knowledge has not been attempted.…”

“…Herroelen et al (1997) illuminate the relation between stochastic NPV maximization and real options theory (Dixit and Pindyck 1994). For the literature on the payment scheduling problem, where the cash flows are themselves decision variables that can be optimized by the project manager or the client, we refer to Padman (1999, 2001), He et al (2012), and Kolisch and Padman (2001).…”

Modelling maintenance scheduling strategies for highway networks

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