Search results for "Fuzzy transportation"

A Fuzzy Chance-constraint Programming Model for a Home Health Care Routing Problem with Fuzzy Demand

2017

The fuzzy p-median problem

2004

In many location models, the strong crisp assumptions, like known demands and distances, are not realistic in most cases. The fuzzy p-median problem relaxes this hypothesis giving to the decision maker a necessary degree of freedom to solve real-world problems. It allows a decision maker to improve an optimal covering of a location problem by considering partially feasible solutions in which some demand is left uncovered. Here we revise the main facts and results about this problem emphasising different specific algorithms of resolution. Finally we show that this fuzzy version can be used to analyse the global structure of a given instance of the crisp problem.

The fuzzy p-median problem: A global analysis of the solutions

2001

Abstract We apply fuzzy techniques to incorporate external data into p-median problems. So we can detect certain solutions that would be discarded by usual crisp and fuzzy algorithms but that contrasted with this additional information can be advantageous. This usually reveals a pathology of the model and hence our methods provide some fuzzy validation criteria for p-median models.

On the equivalence of two optimization methods for fuzzy linear programming problems

2000

Abstract The paper analyses the linear programming problem with fuzzy coefficients in the objective function. The set of nondominated (ND) solutions with respect to an assumed fuzzy preference relation, according to Orlovsky's concept, is supposed to be the solution of the problem. Special attention is paid to unfuzzy nondominated (UND) solutions (the solutions which are nondominated to the degree one). The main results of the paper are sufficient conditions on a fuzzy preference relation allowing to reduce the problem of determining UND solutions to that of determining the optimal solutions of a classical linear programming problem. These solutions can thus be determined by means of classi…

The facility layout problem approached using a fuzzy model and a genetic search

2005

The problem of facility layout design is discussed, taking into account the uncertainty of production scenarios and the finite production capacity of the departments. The uncertain production demand is modelled by a fuzzy number, and constrained arithmetic operators are used in order to calculate the fuzzy material handling costs. By using a ranking criterion, the layout that represents the minimum fuzzy cost is selected. A flexible bay structure is adopted as a physical model of the system while an effective genetic algorithm is implemented to search for a near optimal solution in a fuzzy contest. Constraints on the aspect ratio of the departments are taken into account using a penalty fun…

Viability of infeasible portfolio selection problems: A fuzzy approach

2002

Abstract This paper deals with fuzzy optimization schemes for managing a portfolio in the framework of risk–return trade-off. Different models coexist to select the best portfolio according to their respective objective functions and many of them are linearly constrained. We are concerned with the infeasible instances of such models. This infeasibility, usually provoked by the conflict between the desired return and the diversification requirements proposed by the investor, can be satisfactorily avoided by using fuzzy linear programming techniques. We propose an algorithm to repair infeasibility and we illustrate its performance on a numerical example.

Soft-computing based heuristics for location on networks: The p-median problem

2011

We propose a genetic algorithm for the fuzzy p-median problem in which the optimal transport cost of the associated crisp problem is unknown. Our algorithm works with two populations: in one, the solutions with a better crisp transport cost are favored by the selection criterion, whereas in the second one, solutions with a better fuzzy satisfaction level are preferred. These populations are not independent. On the contrary, the first one periodically invades the second one, thus providing new starting points for finding fuzzy improvements. Our computational results also reveal the importance of choosing adequate functions for selecting the parents. Our best results are obtained with functio…

Marginal analysis for the fuzzy p-median problem

2008

The solutions to the fuzzy p-median problem make it possible to leave part of the demand uncovered in order to obtain significant reductions in costs. Moreover, the fuzzy formulation provides the decision-maker with many flexible solutions that he or she may prefer to the classical crisp solution. We introduce some marginal analysis techniques to study how solutions depend on membership functions. Taking into account the internal structure of the problem, we propose a practical criterion to fix the tolerances for the uncovered demand, which happens to be the most sensitive aspect of the fuzzy p-median.

Solving type-2 assembly line balancing problem with fuzzy binary linear programming

2013

This paper deals with the use of fuzzy set theory as a viable alternative method for modelling and solving the stochastic assembly line balancing problem. This paper presents a fuzzy extension of the simple assembly line balancing problem of type 2 SALBP-2 with fuzzy job processing times since uncertainty, variability, and imprecision are often occurred in real-world production systems. The job processing times are formulated by triangular fuzzy membership functions using their statistical distributions. This study proposes to solve a Fuzzy Binary Linear Problem FBLP with fuzzy coefficients in the objective function and in a constraint. Finally, the effect of the unbalancing of a station in…

An exact algorithm for the fuzzy p-median problem

1999

In this paper we propose a fuzzy version of the classical p-median problem. We consider a fuzzy set of constraints so that the decision-maker will be able to take into account solutions which provide significantly lower costs by leaving a part of the demand uncovered. We propose an algorithm for solving the problem which is based on Hakimi's works and we compare the crisp and the fuzzy approach by means of an example.