A set covering approach to metallurgical grade assignment

Vasko, Francis J.; Wolf, Floyd E.; Stott, Kenneth L.

doi:10.1016/0377-2217(89)90465-7

Cited by 43 publications

(11 citation statements)

References 20 publications

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“…, . , V (2) Desirability Component P is a fuzzy subset of G such that the value of f/G.) is based upon the plant's desirability of producing grade G. This value is based' on factors such as the cost and problems associated with pr6ducing each of the grades and is independent of any particular customer order.…”

Section: Chemistry Componentsmentioning

confidence: 99%

Using fuzzy sets to assign metallurgical grades to steel

Woodyatt

Stott

Wolf

et al. 1992

JOM

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To optimize the productivity and yield of a modern high-speed continuous casting operation, it is desirable to minimize thenumber of metallurgical grades that have to be melted to satisfy a collection of customer orders. This problem has been addressed through the development of an expert system for selecting the set of all potential grades for each order and an optimal selection algorithm for determining the actual grades that would be required to produce all orders. As a further refinement, a fuzzy formulation with a membership function based on the likelihood of a grade meeting the customer's specifications without difficulty has been added. This enables the plate mill to trade off minimizing the number of grades used against maximizing the likelihood that the customer specifications will be met without difficulty.

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Section: Chemistry Componentsmentioning

confidence: 99%

Using fuzzy sets to assign metallurgical grades to steel

Woodyatt

Stott

Wolf

et al. 1992

JOM

Self Cite

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“…Other potential applications are less obvious, however. For example, location models have been used to analyze political party platforms (Hotelling 1929;Ginsberg, Pestieau, and Thisse 1987); archaeological settlement patterns (Bell and Church 1985); location of bank accounts (Cornuejols, Fisher, and Nemhauser 1977); metallurgical grade assignment (Vasko, Wolf, and Stott 1989); selection of ingot sizes (Vasko, Wolf, and Stott 1988); medical diagnosis (Reggia, Nau, and Wang 1983); and data base management (Pirkul 1986).…”

Section: They Include American Journal Of Agricultural Economics; Heamentioning

confidence: 99%

Location Modeling: Perspective and Overview

Current¹,

Schilling

1990

Geographical Analysis

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Since the seminal works of J. H. Von Thiinen and Alfred Weber, the field of location analysis and modeling has attracted the attention of researchers from many disciplines including engineering, logistics, marketing, mathematics, management information systems, operations research, production, regional science, and urban planning. Articles on the topic appear in over fdty academic journals. Continued broad-based interest in location modeling is evident with the recent publication of five books on the topic (Ghosh and McLafferty 1987; Ghosh and Rushton 1987; Berry and Parr 1988; Love, Moms, and Wesolowsky 1988; Hurter and Martinich 1989).The importance of the role that geographers have played in the development of location theory and modeling is clearly evident in the works of the pioneers of the field such as Walter Christaller, Edgar Hoover, August Losch, and Walter Isard. The contribution of geographers to the development of location models has continued with the work of , among others.GeographicaZ Analysis has also played a major role in the development of location modeling by publishing over forty articles on the topic. These articles have had widespread impact. For example, a quick review of the Social Sciences Citation Index revealed that ReVelle and Swain (1970) has been cited over one hundred times in forty different journals, the diversity of which is staggering. They include American Journal of Agricultural Economics; Health Services Review; IEEE Transactions on Computers; IEEE Transactions on Systems, Man and Cybernetics; Industrial Marketing Manugemmt; Lecture Notes in Economics; and Simulation and Games; as well as numerous journals in geography, operations research, planning, and regional science.This broad base of interest is primarily generated by the tremendous number and diversity of potential applications of location models. Clearly, facility location is an important ingredient in the success or failure of many enterprises. Other potential applications are less obvious, however. For example, location models have been used to analyze political party platforms (Hotelling 1929; Ginsberg, Pestieau, and Thisse 1987); archaeological settlement patterns (Bell and Church 1985); location of bank accounts (Cornuejols, Fisher, and Nemhauser 1977); metallurgical John R. Current is associate professor and David A. Schilling is professor of management science, Ohio State University.

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“…SFLA combines the benefits of a genetic-based memetic algorithm and the social behavior-based of particle swarm optimization [14]. The SCP has many practical applications like location of emergency facilities [5], airline and bus crew scheduling [4,18], steel production [13], logical analysis of numerical data [3], ship scheduling [15], vehicle routing [1]. The SCP has been solved using complete techniques and different metaheuristics [20,7,6].…”

Section: Introductionmentioning

confidence: 99%