Client-contractor bargaining problem in the context of multi-mode project scheduling with limited resources

This study focuses on the client-contractor bargaining problem in the context of multimode resource constrained project scheduling. The bargaining objective is to maximize the bargaining objective function comprised of the individual NPV maximizing objectives of both the client and the contractor. Although the well-known multi- mode resource constrained project scheduling problem has been under investigation from various dimensions in the literature, this thesis proposes a two-player setting to this problem. The solution procedure takes the objectives of both players into account. One other proposal we have in this thesis is the bargaining weights concept we have used in the model, which is used to determine the bargaining power of each player through the negotiation process. The effect of bargaining weights assigned to each player on the solution has also been analyzed. Different payment models have also been investigated in this thesis. We have used progress payments, payments at equal time intervals, and payments at activity completions in our tests. Simulated Annealing Algorithm and Genetic Algorithm are proposed as solution procedures. Also the solution set of the problem is investigated by further analyzing the nondominated solutions. We have conducted sensitivity analysis among different parameters we have used in the model. These parameters are profit margin, interest rate, and bargaining weights. The bargaining objective function we have used has been an important part of the model itself. We have investigated different solution approaches by using two different bargaining objective function formulations in our tests

Client-contractor bargaining on net present value in project scheduling with limited resources

The client-contractor bargaining problem addressed here is in the context of a multi-mode resource constrained project scheduling problem with discounted cash flows, which is formulated as a progress payments model. In this model, the contractor receives payments from the client at predetermined regular time intervals. The last payment is paid at the first predetermined payment point right after project completion. The second payment model considered in this paper is the one with payments at activity completions. The project is represented on an Activity-on-Node (AON) project network. Activity durations are assumed to be deterministic. The project duration is bounded from above by a deadline imposed by the client, which constitutes a hard constraint. The bargaining objective is to maximize the bargaining objective function comprised of the objectives of both the client and the contractor. The bargaining objective function is expected to reflect the two-party nature of the problem environment and seeks a compromise between the client and the contractor. The bargaining power concept is introduced into the problem by the bargaining power weights used in the bargaining objective function. Simulated annealing algorithm and genetic algorithm approaches are proposed as solution procedures. The proposed solution methods are tested with respect to solution quality and solution times. Sensitivity analyses are conducted among different parameters used in the model, namely the profit margin, the discount rate, and the bargaining power weights

Client-contractor bargaining on net present value in project scheduling with limited resources

The client-contractor bargaining problem addressed here is in the context of a multi-mode resource constrained project scheduling problem with discounted cash flows, which is formulated as a progress payments model. In this model, the contractor receives payments from the client at predetermined regular time intervals. The last payment is paid at the first predetermined payment point right after project completion. The second payment model considered in this paper is the one with payments at activity completions. The project is represented on an Activity-on-Node (AON) project network. Activity durations are assumed to be deterministic. The project duration is bounded from above by a deadline imposed by the client, which constitutes a hard constraint. The bargaining objective is to maximize the bargaining objective function comprised of the objectives of both the client and the contractor. The bargaining objective function is expected to reflect the two-party nature of the problem environment and seeks a compromise between the client and the contractor. The bargaining power concept is introduced into the problem by the bargaining power weights used in the bargaining objective function. Simulated annealing algorithm and genetic algorithm approaches are proposed as solution procedures. The proposed solution methods are tested with respect to solution quality and solution times. Sensitivity analyses are conducted among different parameters used in the model, namely the profit margin, the discount rate, and the bargaining power weights

Client-contractor bargaining on net present value in the context of a project with limited resources

This study focuses on the client-contractor bargaining problem in the context of multi mode resource constrained project scheduling. The bargaining objective is to maximize the bargaining function comprised of the individual NPV maximizing objectives of both the client and the contractor. Tabu Search and Simulated Annealing are proposed as solution procedures