Suleyman Tufekci

A complete cellular manufacturing system design methodology based on axiomatic design principles

This paper provides a framework and a road map for people who are ready to transform their traditional production system from process orientation to cellular orientation, based on Axiomatic Design (AD) principles. A feedback mechanism for continuous improvement is also suggested for evaluating and improving the cellular design against pre-selected performance criteria. A complete implementation of the proposed methodology at a manufacturing company and resulting performance improvements are also provided.

Modeling of building evacuation problems by network flows with side constraints

Abstract In this paper we model building evacuations by network flows with side constraints. Side constraints come from variable arc capacities on some arcs which are functions of flows in incident arcs. In this context we study maximum flow, minimum cost, and minimax objectives. For some special structured networks we propose ‘greedy’ algorithms for solving these problems. For more general network structures, solution procedures are recommended which take advantage of the network structures of the problems.

An integrated emergency management decision support system for hurricane emergencies

Hurricane Andrew has taught Florida a deadly and expensive lesson. Once again, we have been reminded how unprepared we are for natural disasters. In this paper we present a conceptual framework for an effective, integrated, and modular decision support system (DSS) for hurricane emergency management. As an important component of this decision support system, we have been developing a PC-based emergency hurricane evacuation planning module, Regional Evacuation Modeling System (REMS), at the University of Florida since 1990. The software uses simulation as well as several network optimization models in estimating the evacuation time and the traffic flow on a given transportation road network. The system is very robust and user friendly. One of the important features of REMS is its ability to be used in real time.

On the use of lexicographic min cost flows in evacuation modeling

Building evacuation problems can be represented as dynamic network-flow problems [3]. The underlying network structure of a building evolves through time yielding a time-expanded network (a dynamic network). Usually in such evacuation problems involving time, more than one objective function is appropriate. For example, minimizing the total evacuation time and evacuating a portion of the building as early as possible are two such objectives. In this article we show that lexicographical optimization is applicable in handling such multiple objectives. Minimizing the total evacuation time while avoiding cyclic movements in a building and priority evacuation are treated as lexicographical min cost flow problems. Language: en

Regional Evacuation Modeling System (REMS): A decision support system for emergency area evacuations

Abstract In this paper we present a decision support system being developed at the University of Florida. The system is a PC-based software package that is capable of testing different emergency scenarios due to hurricanes, chemical accidents or nuclear accidents. The underlying models are optimization models based on a regional transportation network. One of the most significant aspects of the software is its ability to handle time dimension of the problem explicitly. It is this aspect of REMS that makes incorporation at any time of road blockages due to the presence of extremely hazardous substances or inundation of roads due to accidents or flooding possible in evacuation scenarios tested. The software has the ability to animate the evacuation process in time and display the flow of traffic on the links of the transportation network in a time-lapsed manner with color codes. Additionally REMS is also capable to animate the progress of the plume exposure pathway of an extremely hazardous substances as it evolves in time onto the evacuation network and to display the dynamic vehicle flow in time simultaneously.

Solving time/cost trade-off problems with discounted cash flows using generalized benders decomposition

In this article we consider a project scheduling problem where there are cash flows throughout the life of the project and where shorter activity durations can be attained by incurring greater direct costs. In particular, the objective of this problem is to determine the activity durations and a schedule of activity start times so that the net present value of cash flows is maximized. We formulate this problem as a mixed-integer nonlinear program which is amenable to solution using the generalized Benders decomposition technique developed by Geoffrion. We test the algorithm on 140 project scheduling problems, the largest of which contains 30 nodes and 64 activities. Our computational results are quite encouraging inasmuch as 123 of the 140 problems require less than 1 CPU second of solution time.

A genetic algorithm for the talent scheduling problem

Abstract We present the talent scheduling problem and provide several hybrid genetic search algorithms for solving this problem. The problem is of scheduling the independent activities of a project (such as a movie) so that the cost of keeping talents (actors) on the project site when not needed is minimized. The problem is an NP-hard problem. The proposed hybrid algorithms use limited pairwise interchange heuristic procedure within the simple genetic algorithm framework. We report very impressive results on a set of problems with known optimal solutions.

Block‐vertex duality and the one‐median problem

The w-centroid problem, denoted by (C), is an optimization problem which has been shown by Kariv and Hakimi to be equivalent, on a tree graph, to the 1-median location problem, denoted by (M). For a general (weighted) connected graph G we develop a duality between (C) (which is defined on G) and a block optimization problem, denoted by (B), and defined over the blocks of G. A block is a maximal nonseparable subgraph. We analyze (B) and (C) by means of two problems equivalent to (B) and (C) respectively, but defined on a blocking graph G which is always a tree. We give an O(∣V∣) algorithm to solve the two problems on G, and we characterize the solutions. We also show that the solution to a 1-median problem defined on G either solves (M) on the original graph G or localizes the search for a solution to (M) to the vertices of a single block. We introduce an extended version of Goldmans algorithm which (in linear time) either solves (M) on G, or finds the single block of G which contains all solutions to (M).

Analysis and solution to the single-level batch production smoothing problem

Many companies use mixed-model production systems running under the Just-in-Time philosophy in order to efficiently meet customer demands for a variety of products. Such systems require demand be stable and production sequence be leveled. The production smoothing problem aims at finding level schedules in which the appearances of products are dispersed over the horizon as uniformly as possible. In this paper, the production smoothing problem is extended to a more general manufacturing environment where a single machine can be identified as either the final or the bottleneck stage of the system and products may have arbitrary non-zero setup and processing time requirements on this single machine. An optimization model is built for the problem and a two phase solution methodology is developed. The first phase problem is shown to be NP-hard and a parametric heuristic procedure is proposed for its solution. In contrast, the second phase problem is shown to be efficiently solvable and currently available solution methods are adopted from the literature. A computational study is designed to test the proposed two phase solution methodology and also the parametric heuristic procedure. Computational results show that the proposed two phase solution methodology enables effective and efficient control of the studied manufacturing system, and the heuristic procedure developed for the first phase problem is time efficient and promises near optimal solutions for a variety of test instances.

Optimizing production smoothing decisions via batch selection for mixed-model just-in-time manufacturing systems with arbitrary setup and processing times

This paper is concerned with the production smoothing problem that arises in the context of just-in-time manufacturing systems. The production smoothing problem can be solved by employing a two-phase solution methodology, where optimal batch sizes for the products and a sequence for these batches are specified in the first and second phases, respectively. In this paper, we focus on the problem of selecting optimal batch sizes for the products. We propose a dynamic programming (DP) algorithm for the exact solution of the problem. Our computational experiments demonstrate that the DP approach requires significant computational effort, rendering its use in a real environment impractical. We develop three meta-heuristics for the near-optimal solution of the problem, namely strategic oscillation, scatter search and path relinking. The efficiency and efficacy of the methods are tested via a computational study. The computational results show that the meta-heuristic methods considered in this paper provide near-optimal solutions for the problem within several minutes. In particular, the path relinking method can be used for the planning of mixed-model manufacturing systems in real time with its negligible computational requirement and high solution quality.