Sharif Digital Repository

In this paper, we study a resource-constrained project scheduling problem in which a set of project activities have due dates. If the finish time of each one of these activities is not equal to its due date, an earliness or a tardiness cost exists for each tardy or early period. The objective is to minimize the sum of discounted weighted earliness-tardiness penalty costs of these activities. Scatter Search algorithm is used to deal with this extended form of resource-constrained project scheduling problem. Our implementation of Scatter Search integrates the advanced methods such as dynamic updating of the reference set and the use of frequency-based memory within the diversification... 

Project scheduling to maximize the net present value of the cash flows has been a topic of recent research. These researches assume that the duration of activities is known either with certitude or at least with some probability. However, in many applications the structure of the duration of activities is imprecise. In this paper, the project scheduling problem with discounted cash flows under fuzzy environment is considered. The duration of activities are assumed triangular fuzzy numbers. The derived mathematical model is a multi-objective non-linear programming model and for solving it the Taylor expansion is used to transform the objective function to a linear form. To interpret the fuzzy... 

A resource investment problem with discounted cash flows is a project scheduling problem in which the availability levels of the resources are considered decision variables and the goal is to find a schedule and resource requirement levels such that the net present value of the project cash flows optimizes. In this paper, we present a genetic algorithm to solve this problem. We explain the elements of the algorithm such as chromosome structure, fitness function, crossover, mutation, and local improvement operations and solve more than 220 problems with known optimal solutions to evaluate the performance of the proposed algorithm. The results of the experimentation are quite satisfactory. ©... 

A resource investment problem with discounted cash flows (RIPDCF) is a project-scheduling problem in which (a) the availability levels of the resources are considered decision variables and (b) the goal is to find a schedule such that the net present value of the project cash flows optimizes. In this paper, the RIPDCF in which the activities are subject to generalized precedence relations is first modeled. Then, a genetic algorithm (GA) is proposed to solve this model. In addition, design of experiments and response surface methodology are employed to both tune the GA parameters and to evaluate the performance of the proposed method in 240 test problems. The results of the performance... 

This research considers a project scheduling problem with the object of minimizing weighted earliness-tardiness penalty costs, taking into account a deadline for the project and precedence relations among the activities. An exact recursive method has been proposed for solving the basic form of this problem. We present a new depth-first branch and bound algorithm for extended form of the problem, which time value of money is taken into account by discounting the cash flows. The algorithm is extended with two bounding rules in order to reduce the size of the branch and bound tree. Finally, some test problems are solved and computational results are reported. © 2008 Asian Network for Scientific... 

A resource investment problem is a project-scheduling problem in which the availability levels of the resources are considered as decision variables and the goal is to find a schedule, and resource requirement levels, such that some objective function optimizes. In this paper, we consider a resource investment problem in which the goal is to maximize the net present value of the project cash flows. We call this problem as Resource Investment Problem with Discounted Cash Flows (RIPDCF) and we develop a heuristic method to solve it. Results of several numerical examples show that the proposed method performs relatively well  

Optimal well placement is a crucial step in reservoir development process. The key points in such an optimization process are using a fast function evaluation tool and development of an efficient optimization algorithm. This study presents an approach that uses particle swarm optimization algorithm in conjunction with streamline simulation to determine the optimum well locations within a reservoir, regarding a modified net present value as the objective. Performance of this algorithm was investigated through several different examples, and compared to that of genetic algorithm (GA) and simulated annealing (SA) methods. It was observed that particle swarm optimization algorithm outperformed... 

Distribution companies are pressurized into investing in many projects for ensuring customer satisfaction and increasing their profitability. There are a lot of feasible projects that may help companies to improve their services, but resources for accomplishing them are limited. Therefore, financial subjects are crucially important for related decision making and budget allocation is a bone of contention between different departments of companies. Project net present value (NPV), which depends on investment, expected annual profit, interest rate and inflation rate, is realistic criterion of project economic value. Interest rate and inflation rate are not predefined coefficients.... 

Traditionally, the model of a resource-constrained project-scheduling problem (RCPSP) contains a single objective function of either minimizing project makespan or maximizing project net present value (NPV). In order to be more realistic, in this paper, two multi-objective meta-heuristic algorithms of multi-population and two-phase sub-population genetic algorithms are proposed to find Pareto front solutions that minimize the project makespan and maximize the project NPV of a RCPSP, simultaneously. Based on standard test problems constructed by the RanGen project generator, a comprehensive computational experiment is performed, where response surface methodology is employed to tune the... 

A mixed binary integer mathematical programming model is developed in this paper for ordering items in multi-item multi-period inventory control systems, in which unit and incremental quantity discounts as well as interest and inflation factors are considered. Although the demand rates are assumed deterministic, they may vary in different periods. The situation considered for the problem at hand is similar to a seasonal inventory control model in which orders and sales happen in a given season. To make the model more realistic, three types of constraints including storage space, budget, and order quantity are simultaneously considered. The goal is to find optimal order quantities of the... 

Optimization of any production operation is a tool for increasing production rates and reducing production costs. Water flooding is one of the techniques that frequently be used to increase oil recovery after primary depletion. A methodology for optimizing the production by using the net present value of a heterogeneous reservoir under water flooding has been presented, which is based on controlling the bottomhole pressures of the production wells, using smart well technology. For this purpose, a numerical flow simulator is coupled with an optimization program. The technique was implemented on a synthetic two dimensional oil reservoir with heterogeneous permeability. This optimization... 

Water and miscible gas injection scenarios are considered in an Iranian oil reservoir for the purpose of recovery improvement. Firstly reservoir fluid modeling and modeling of a slim tube test were performed. Then, water alternating gas (WAG) injection was evaluated by optimizing the WAG half cycle and WAG ratio. Alternatively, hybrid WAG and separate injection of water and gas in the top and bottom of the reservoir were also investigated. The numerical simulation results showed that the optimum WAG, with half cycle of 1.5 years and WAG ratio of one, gave the highest recovery factor. Moreover, economic evaluation of these scenarios indicated that WAG had the highest net present value and was... 

Water and miscible gas injection scenarios are considered in an Iranian oil reservoir for the purpose of recovery improvement. Firstly reservoir fluid modeling and modeling of a slim tube test were performed. Then, water alternating gas (WAG) injection was evaluated by optimizing the WAG half cycle and WAG ratio. Alternatively, hybrid WAG and separate injection of water and gas in the top and bottom of the reservoir were also investigated. The numerical simulation results showed that the optimum WAG, with half cycle of 1.5 years and WAG ratio of one, gave the highest recovery factor. Moreover, economic evaluation of these scenarios indicated that WAG had the highest net present value and was... 

In order to develop a more realistic resource-constrained project-scheduling model that is applicable to real-world projects, in this paper, the resource investment problem with discounted cash flows and generalized precedence relations is investigated under inflation factor such that a bonus-penalty structure at the deadline of the project is imposed to force the project not to be finished beyond the deadline. The goal is to find activity schedules and resource requirement levels that maximize the net present value of the project cash flows. The problem is first mathematically modeled. Then, a genetic algorithm (GA) is designed using a new three-stage process that utilizes design of... 

The facility location problem and its related financial issues have a significant impact on the configuration of a supply chain structure (SCS). Although affording the setup cost of facilities requires a huge financial investment, a meticulous planning to recoup it has been neglected by an overwhelming majority of previous studies. To fill this gap, an economical investment plan of facilities is determined by striking a trade-off between the contribution of the stockholders’ capital and the loan arrangement. In the context of a multiperiod three-echelon SCS, the model also determines the optimum location of plants and the best supply and distribution patterns. The model maximizes the fill...