Project Delivery of Goods With Limited Resources and Minimum Time Using Fuzzy Logic Method

Abstract

               In solving the problem of fuzzy application for scheduling delivery of goods with a limited power source and minimal time, the problems that are still not considered in the RCPS problem modeling are the uncertainty characteristics of the parameters of the timing of activities in the delivery project. Even though this can be solved by using the PERT (Project Evaluation and Review Technoloque) method with a probabilistic approach, this technique still ignores the limitations of the supply of resources. Actually, a probabilistic approach can be used, if previously provided data about the experience in completing similar projects. But if the project is a new project or the techniques and methodologies used to complete a new project, such as new techniques and methodologies in software engineering, among others: object-oriented design and programming, computer-aided software design, user interface management systems, fourth generation languages, etc., then the probabilistic approach is not suitable.                   

In this situation, the decision maker must be able to estimate the cost and time duration, of all activities in the project based on existing experience, related to the level of knowledge they have, about new techniques and methodologies to be applied, and the level of human resource expertise. which are available.     This method of estimating project costs and time, which is more precise, uses representations in the form of fuzzy numbers, namely fuzzy sets in the set of real numbers that are normal, convex, and closed intervals. The delivery time is modeled as a fuzzy number of LR types IKiri, IKanan, α, β, with three values ​​of α-cuts E = 0.3, L = 0.7, and I = 1.0. The fuzzy transformation model is based on three pairs of inferior and superior values ​​from α-cuts. The priority for scheduling delivery of goods is based on the smallest early start time EST value. Resources are solved by serial and parallel models. The smallest makespan value is used to determine the best solution. Goods delivery settlement uses fuzzy operations, namely arithmetic operations and relation operations.                   

Analysis of the output oftware based on testing with test scenarios (table ^ .50) for some input data shows that the parallel method is better than the serial method. This is indicated by the large difference in makespan value generated from the two methods. Based on input data from a software development project, the serial method gives makespan values ​​in the range between 675.0 and 867.0, while the parallel method gives makespan values ​​in the range between 116.0 and 259.0. The analysis of the output software in a fuzzy Gantt Chart representation shows that an activity can be scheduled with varying degrees of optimism. The degree of optimistic activity scheduling can be graded in linguistic terminology between two extreme pessimistic and optimistic values, namely very pessimistic, pessimistic, slightly pessimistic, slightly optimistic, optimistic, very optomistic.