Tolunay Göçken

Multi-objective aggregate production planning with fuzzy parameters

In this paper, a direct solution method that is based on ranking methods of fuzzy numbers and tabu search is proposed to solve fuzzy multi-objective aggregate production planning problem. The parameters of the problem are defined as triangular fuzzy numbers. During problem solution four different fuzzy ranking methods are employed/tested. One of the primary objectives of this study is to show that how a multi-objective aggregate production planning problem which is stated as a fuzzy mathematical programming model can also be solved directly (without needing a transformation process) by employing fuzzy ranking methods and a metaheuristic algorithm. The results show that this can be easily achieved.

Solution of a fully fuzzy multi-item economic order quantity problem by using fuzzy ranking functions

In this study, a fuzzy multi-item economic order quantity (EOQ) problem is solved by employing four different fuzzy ranking methods. All of the parameters of the multi-item EOQ problem are defined as triangular fuzzy numbers. Fuzzy ranking methods are used to rank the fuzzy objective values and to handle the constraints in the model. The results obtained by employing different fuzzy ranking methods are also compared.

A direct solution approach to fuzzy mathematical programs with fuzzy decision variables

In this paper, a direct solution approach is presented for solving fuzzy mathematical programming problems with fuzzy decision variables. In the proposed approach, a fuzzy ranking procedure for fuzzy numbers and a meta-heuristic algorithm is employed. A basic example is presented in the paper. It has been observed that fuzzy mathematical programs with fuzzy decision variables can be solved effectively by employing direct solution approaches which are based on fuzzy ranking procedures and meta-heuristics.

Solving fully fuzzy mathematical programming model of EOQ problem with a direct approach based on fuzzy ranking and PSO

Inventory management is critical for many industries. A proper control of inventory can considerably enhance a companys profit margins. Determination of the Economic Order Quantities EOQ is important in order to achieve optimal operating conditions. There are various EOQ models which originate from the classical EOQ model in the literature. In reality, it is not easy to determine parameters of an EOQ model precisely. Fuzzy set theory gives an opportunity to represent the linguistic terms and vagueness in EOQ models. In the literature, various researchers solved different fuzzy versions of EOQ problem. In this study, a fully fuzzy constrained multi-item EOQ model is considered. The parameters of the problem are defined as triangular fuzzy numbers. The fuzzy constrained multi-item EOQ problem is tried to be solved directly by employing four different fuzzy ranking functions and Particle Swarm Optimization PSO algorithm. One of the primary objectives of this study is to show that fuzzy mathematical programming models can also be solved directly by employing fuzzy ranking functions and meta-heuristic algorithms. Results obtained from both approaches direct approach and transformation approach are also reported in the paper.

A tabu search approach to fuzzy goal programs and an application to aggregate production planning

In this article, a multiple-objective tabu-search-based solution method is developed to solve fuzzy goal programs. The application of the method is shown on a fuzzy aggregate production-planning problem. Extensive computational work is carried out to present the performance of the algorithm and the effect of its parameters on the solution quality.

A fuzzy approach for the reviewer assignment problem

Abstract Assignment of experts to project proposals is a significant task for funding agencies which have to assess the potential value of the research and development (RD the problem can be defined as assigning the most suitable experts to the proposals under some constraints, which are generally encountered by funding agencies. In this study, a fuzzy model is offered to solve the reviewer assignment problem. The objective of the model is to maximize the total matching degree of assigned experts under some constraints such as cost of forming a panel and the size of a panel. The matching degrees are defined using linguistic variables to denote the expertise of each expert with respect to each proposal. The fuzzy mathematical model, which also takes into account different constraints related to the problem, is solved via the selected fuzzy ranking methods namely; the signed distance method and the method of ranking fuzzy numbers with integral value. The solution of an example problem – inspired from a real-life situation – with both of the mentioned methods revealed the effectiveness of the solution approach. It is believed that the use of the offered fuzzy approach could improve the accuracy of the decisions made by funding agencies.

Solution of fuzzy multi-objective project crashing problem

Project management is a very important field employed for scheduling activities and monitoring the progress, in competitive and fluctuating environments. The feasible duration time required to perform a specific project is determined using critical path method. However, because of competitive priorities, time is important and the completion time of a project determined using critical path method should be reduced to meet a deadline requested. In this situation, project crashing problem arises. Project crashing analysis is concerned with shortening the project duration time by accelerating some of its activities at an additional cost. In general, the parameters of the problem are accepted as certain and the project crashing problems are solved using deterministic solution techniques. In reality, because of uncertain environment conditions, incomplete or unobtainable information, there can be ambiguity in the parameters of the problem. The uncertainty in the parameters can be modeled via fuzzy set theory. Using fuzzy models gives the chance of better project management decisions with more stability under uncertain environmental factors. In the literature, various authors solved different fuzzy versions of project management problems via transforming them into their crisp equivalents. In this study, a fuzzy multi-objective project crashing problem with fuzzy parameters is handled. The fuzzy project crashing problem is solved with a direct solution approach based on fuzzy ranking methods and the tabu search algorithm.

A PRACTICAL APPROACH TO PRIORITIZE PROJECT ACTIVITIES THROUGH FUZZY RANKING

Effective management of project activities is a critical issue for project managers, especially when the projects are complex. This is more essential for projects where the number of activity attributes is numerous. In such circumstances, prioritizing of project activities is an important issue and can enable better management of projects by focusing more on the most critical activities. However, in many cases prioritizing project activities can be a difficult task because some of the activity attributes might not be expressed easily in crisp terms. In this article, a practical fuzzy rating and ranking approach is proposed to prioritize project activities with fuzzy attributes. The proposed approach is also tested through an example problem from the literature.

Solving Fuzzy Multi-Item Economic Order Quantity Problems via Fuzzy Ranking Functions and Particle Swarm Optimization

Determination of the Economic Order Quantities (EOQ) is critical for many service and manufacturing industries in order to achieve optimal operating conditions. Although there are numerous studies on solving EOQ problems with crisp parameters, the number of studies which consider EOQ problems with fuzzy parameters is very limited in the literature. In this paper, a multi-item EOQ problem with fuzzy parameters is considered. All of the parameters of the multi-item EOQ problem are defined as triangular fuzzy numbers. Afterwards the fully fuzzy 11 mathematical programming problem is solved directly (without any transformation process) by making use of fuzzy ranking functions and the particle swarm optimization algorithm. It is observed that the proposed approach is eligible in solving the present problem.

Direct Solution of Fuzzy Project Crashing Problem with Fuzzy Decision Variables using Tabu Search and Simulated Annealing Algorithms

Project management is a very important field employed for scheduling activities and monitoring the progress, in competitive and fluctuating environments. Project crashing analysis is concerned with shortening the project duration time by accelerating some of its activities at an additional cost. In reality, because of uncertain environment conditions there can be ambiguity in the parameters of the problem. The uncertainty in the parameters can be modeled via fuzzy set theory. Using fuzzy models give the chance of better project scheduling with more stability under uncertain environmental factors. In this study, a fuzzy project crashing problem with fuzzy decision variable-occurrence time of events-and fuzzy normal activity duration times is handled. The fuzzy project crashing problem is solved without any transformation process by employing a fuzzy ranking method and the tabu search and simulated annealing algorithms.