Results 1  10
of
20
Facility Location under Uncertainty: A Review
 IIE Transactions
, 2004
"... Plants, distribution centers, and other facilities generally function for years or decades, during which time the environment in which they operate may change substantially. Costs, demands, travel times, and other inputs to classical facility location models may be highly uncertain. This has made th ..."
Abstract

Cited by 77 (7 self)
 Add to MetaCart
Plants, distribution centers, and other facilities generally function for years or decades, during which time the environment in which they operate may change substantially. Costs, demands, travel times, and other inputs to classical facility location models may be highly uncertain. This has made the development of models for facility location under uncertainty a high priority for researchers in both the logistics and stochastic/robust optimization communities. Indeed, a large number of the approaches that have been proposed for optimization under uncertainty have been applied to facility location problems. This paper reviews the literature...
Stochastic pRobust Location Problems
, 2004
"... Many objectives have been proposed for optimization under uncertainty. The typical stochastic programming objective of minimizing expected cost may yield solutions that are inexpensive in the long run but perform poorly under certain realizations of the random data. On the other hand, the typical ro ..."
Abstract

Cited by 22 (4 self)
 Add to MetaCart
Many objectives have been proposed for optimization under uncertainty. The typical stochastic programming objective of minimizing expected cost may yield solutions that are inexpensive in the long run but perform poorly under certain realizations of the random data. On the other hand, the typical robust optimization objective of minimizing maximum cost or regret tends to be overly conservative, planning against a disastrous but unlikely scenario. In this paper, we present facility location models that combine the two objectives by minimizing the expected cost while bounding the relative regret in each scenario. In particular, the models seek the minimumexpectedcost solution that is probust; i.e., whose relative regret is no more than 100p% in each scenario.
Random Keys Genetic Algorithm with Adaptive Penalty Function for Optimization of Constrained Facility Layout Problems
, 1997
"... This paper presents an extended formulation of the unequal area facilities block layout problem which explicitly considers uncertainty in material handling costs by use of expected value and standard deviations of product forecasts. This formulation is solved using a random keys genetic algorith ..."
Abstract

Cited by 12 (2 self)
 Add to MetaCart
This paper presents an extended formulation of the unequal area facilities block layout problem which explicitly considers uncertainty in material handling costs by use of expected value and standard deviations of product forecasts. This formulation is solved using a random keys genetic algorithm (RKGA) to circumvent the need for repair operators after crossover and mutation. Because this problem can be highly constrained depending on the maximum allowable aspect ratios of the facility departments, an adaptive penalty function is used to guide the search to feasible, but not suboptimal, regions. The RKGA is shown to be a robust optimizor which allows a user to make an explicit characterization of the cost and uncertainty tradeoffs involved in a particular block layout problem.
Design of Flexible Plant Layouts
 IIE Transactions
, 2000
"... In this paper, we address the problem of designing flexible plant layouts for manufacturing facilities where product demands are subject to variability. A flexible layout is one that maintains low material handling costs despite fluctuations in the product demand levels. We extend existing procedure ..."
Abstract

Cited by 9 (1 self)
 Add to MetaCart
(Show Context)
In this paper, we address the problem of designing flexible plant layouts for manufacturing facilities where product demands are subject to variability. A flexible layout is one that maintains low material handling costs despite fluctuations in the product demand levels. We extend existing procedures for design of flexible layouts by (1) explicitly capturing the stochastic nature of product demands and the resulting variability in material flows between different processing departments, (2) allowing for the possibility of multiple processing departments of the same type to exist in the same facility, and (3) letting material flows between pairs of individual departments be determined simultaneously with the layout and as a function of demand scenarios. Optimal and heuristic methods are presented for generating flexible layouts and determining flow allocations under various design and operation assumptions. 2 1. Introduction The ability to design and operate manufacturing facilitie...
DESIGN OF A MANUFACTURING FACILITY LAYOUT WITH A CLOSED LOOP CONVEYOR WITH SHORTCUTS USING QUEUEING THEORY AND GENETIC ALGORITHMS
"... Most current manufacturing facility layout problem solution methods aim at minimizing the total distance traveled, the material handling cost, and/or the time spent in the system (based on distance traveled at a specific speed). The methodology proposed in this paper solves the looped layout design ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
Most current manufacturing facility layout problem solution methods aim at minimizing the total distance traveled, the material handling cost, and/or the time spent in the system (based on distance traveled at a specific speed). The methodology proposed in this paper solves the looped layout design problem for a looped layout manufacturing facility with a looped conveyor material handling system with shortcuts by using the operational performance metric, i.e. the workinprocess on the conveyor in a manufacturing facility, as the design criterion. 1
Facility Location: A Robust Optimization Approach
"... I n this research, we apply robust optimization (RO) to the problem of locating facilities in a network facing uncertaindemand over multiple periods. We consider a multiperiod fixedcharge network location problem for which we find (1) the number of facilities, their location and capacities, (2) th ..."
Abstract

Cited by 3 (1 self)
 Add to MetaCart
I n this research, we apply robust optimization (RO) to the problem of locating facilities in a network facing uncertaindemand over multiple periods. We consider a multiperiod fixedcharge network location problem for which we find (1) the number of facilities, their location and capacities, (2) the production in each period, and (3) allocation of demand to facilities. Using the RO approach we formulate the problem to include alternate levels of uncertainty over the periods. We consider two models of demand uncertainty: demand within a bounded and symmetric multidimensional box, and demand within a multidimensional ellipsoid. We evaluate the potential benefits of applying the RO approach in our setting using an extensive numerical study. We show that the alternate models of uncertainty lead to very different solution network topologies, with the model with box uncertainty set opening fewer, larger facilities. Through sample path testing, we show that both the box and ellipsoidal uncertainty cases can provide small but significant improvements over the solution to the problem when demand is deterministic and set at its nominal value. For changes in several environmental parameters, we explore the effects on the solution performance. Key words: facility location; robust optimization; uncertainty; robust counterpart
Robust 1median location problem on a tree
 In Proceedings of the ORP3 meeting
, 2005
"... Abstract — In combinatorial optimization, and particularly in location problems, the most used robustness criteria rely either on maximal cost or on maximal regret. However, it is well known that these criteria are too conservative. In this paper, we present a new robustness approach, called lexico ..."
Abstract

Cited by 2 (1 self)
 Add to MetaCart
(Show Context)
Abstract — In combinatorial optimization, and particularly in location problems, the most used robustness criteria rely either on maximal cost or on maximal regret. However, it is well known that these criteria are too conservative. In this paper, we present a new robustness approach, called lexicographic αrobustness, which compensates for the drawbacks of the criteria based on the worst case. We apply this notion to the 1median location problem under uncertainty and we give a polynomial algorithm to determine robust solutions in the case of a tree graph. Index Terms — Robustness, 1median location problem, minmax cost/regret, scenariobased uncertainty.
Considering Production Uncertainty In Block Layout Design
, 1999
"... This paper presents a formulation of the facilities block layout problem which explicitly considers uncertainty in material handling costs by use of expected values and standard deviations of product forecasts. This formulation is solved using a genetic algorithm metaheuristic with a flexible ba ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
This paper presents a formulation of the facilities block layout problem which explicitly considers uncertainty in material handling costs by use of expected values and standard deviations of product forecasts. This formulation is solved using a genetic algorithm metaheuristic with a flexible bay construct of the departments and total facility area. It is shown that depending on the attitude of the decisionmaker towards uncertainty, the optimal layout can change significantly. Furthermore, designs can be optimized directly for robustness over a range of uncertainty that is prespecified by the user. Keywords  facilities, heuristics, optimisation, genetic algorithms, block layout, production uncertainty 1. Introduction Facility design problems generally involve the partition of a planar region into departments (work centers or cells) along with an aisle structure and a material handling system to link the departments. The primary objective of the design problem is to minimi...