A goal programming approach to multi-period production line scheduling

doi:10.1016/0305-0548(78)90026-6

Computers & Operations Research

Volume 5, Issue 3, 1978, Pages 205-211

https://doi.org/10.1016/0305-0548(78)90026-6 Get rights and content

Abstract

This paper considers the problem of scheduling multiple products on several different production lines (i.e. the n-job, m-machine scheduling problem) when multiple objectives exist. Specifically a goal programming model is developed and demonstrated via a case example. The production setting modeled in this paper includes three separate production lines that merge into a single inspection facility. Prior to the description and demonstration of the goal programming model, a brief overview of the multi-product scheduling problem and the various solution approaches to the problem is presented.

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Cited by (20)

Production scheduling using a multi-objective framework in an automotive company
2021, IFAC-PapersOnLine
The increased demand for highly customized products and the need for shortening lead times for competitive advantage has also affected the automotive industry. Companies that handle markets in a multi-faced network of demand, like Europe, need to be flexible, responsive, and follow a customer-focused policy. Therefore, there is an increased need for automated solutions not only in product design but also in the manufacturing section. Such solutions need to replace manual effort increasing efficiency and creating new horizons of innovation and development. In this paper, a mathematical model based on Goal Programming modeling has been introduced as a part of a more flexible and automated perspective for production scheduling. The model is applied to a production scheduling process of an automotive company headquartered in Germany to handle a multi-objective problem that manual effort cannot. The paper will explain how demand management, lead time shortening, and process efficiency can be solved through a mathematical model properly modified to its cause.
Goal programming model: A glorious history and a promising future
2001, European Journal of Operational Research
Citation Excerpt :
Let us cite some new developments which could lead to future research and new applications. The GP model was popularized with the applications by Lee (1972, 1973), Lee and Clayton (1972); Lee et al. (1978) and Ignizio (1978). Among the main applications of the GP we can mention the following: Management of the Reservoir Watershed (Chang et al., 1997), Management of Solid Wastes (Chang and Wang, 1997), Accounting and Financial Resources Management (Cook, 1984; Sharda and Musser, 1986; Aderoba, 1994; Cooper et al., 1997), Marketing and Quality Control (Sengupta, 1981), Human Resources (Price, 1974; Price and Gravel, 1984), Production (Lee et al., 1978; Decro, 1984; Schniederjans and Hong, 1996; Aouni et al., 2000), Transportation and Facility Location (Min, 1988, 1989; Martel and Aouni, 1992; Charnes et al., 1996), Transportation Problems Subject to Budget Restraints (Chalam, 1994), Spatial Studies (Athanassopoulos, 1996), Telecommunications (Sueyoshi, 1996), Agriculture and Forestry (Sinha et al., 1988; Romero, 1991; Pickens and Hof, 1991), Industrial Applications (Rao, 1987a,b; Dhingra et al., 1990; Rao et al., 1992; Gen et al., 1993), Vehicles Park Management (Goghrod et al., 2000) as well as Aviation (Suzuki and Yoshizawa, 1994).
In the last 40 years, there has been a marked transformation in the development of new methodologies to assist the decision-making process, especially in the development of procedures in multi-criterion decision-making and in multi-objective programming (MOP). Goal programming (GP) is the most commonly known model of MOP and it is today alive more than ever, supported by a network of researchers and practitioners continually feeding it with theoretical developments and applications, all of these with resounding success. This paper paints a picture summarizing the history of GP and suggests a few areas of research in this era of globalization.
Multiple criteria decision support system for production management
1990, Engineering Costs and Production Economics
A microcomputer-based decision support system (DSS) is developed to help the managers of medium-scale firms make decisions when faced with rapidly changing market conditions and to strengthen their production management problem-solving abilities. The system, designed for production management, includes three basic units: (i) the database, an information resource; (ii) the model base, a solution technique; and (iii) the interactive dialogue, a decision making procedure.
The database subsystem integrates the advantages of using a structure database to convert manual operations to computerized operations and provides up-to-date information. The model base subsystem is designed to minimize the inventory cost by considering two objectives. A heuristic procedure is also introduced to solve the large scale bicriterion integer programming model when used in a real production environment. The man-machine interactive dialogue is designed to allow communication with the system in an easily learned and approachable manner. The entire DSS is based on the practical operations of a medium-scale export commodity producer.
A goal approach to assembly line balancing
1990, Computers and Operations Research
A zero-one goal programming model for the assembly line balancing problem is developed. The goal model provides increased flexibility in constructing line balances by simultaneously considering varying operational requirements, such as zoning, sequencing, idle time, cycle time and costs. A sensitivity analysis of an example model highlights the usefulness of the approach in the planning stages of a line balance development.
Production planning & scheduling. Computational feasibility of multi-criteria models of production, planning and scheduling
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This paper surveys the applications of multi-criteria decision making (MCDM) methods to production planning, scheduling, and sequencing problems. The basic structure of the decision models are described by their objectives and the resulting models are classified by decision variables into the areas of Aggregate Production Planning, Disaggregate Production Planning, Production Scheduling, and Single Machine Sequencing. The problem sizes that have been solved are summarized to determine how practical it is to use MCDM.
Multiple objective decision making on the microcomputer for production/operations management: An overview
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^∗: Sang M. Lee is Professor and Chairman of the Department of Management at the University of Nebraska at Lincoln. He received the Ph.D. in Management Science from the University of Georgia, and an M.B.A. from Miami University of Ohio. He is currently Series Editor of the Modern Decision Analysis Series, Petrocelli/Charter Publishers, Inc. His books published include Goal Programming for Decision Analysis (1972), Introduction to Decision Science (1975), with L. J. Moore, and Linear Optimization for Management (1976). In addition, he has published over sixty articles in such journals as Decision Sciences, Management Science, Journal of Finance, AIIE Transactions, Sloan Management Review and numerous others. He is a member of TIMS, ORSA and AIDS; currently serving as Secretary of AIDS, and has previously served as Vice President and President of National AIDS and Southeast AIDS respectively.

^†: Edward R. Clayton is Professor and Coordinator of Management Science at Virginia Polytechnic Institute and State University, Blacksburg, Virginia. He received a B.S. from the University of Florida and a Ph.D. from Clemson University in Engineering Management. He is a co-author of GERT Modeling and Simulation: Fundamentals and Applications, published by Petrocelli/Charter in 1976. He is a charter member of AIDS and a member of TIMS and is currently chairman of S.E. TIMS. His research interests are in network analysis, simulation, and applications of mathematical programming. He has published numerous articles in journals including Management Science, Journal of Marketing and others. He serves as a consultant to the U.S. Army Concepts Analysis Agency on math programming and simulation.

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PaperA goal programming approach to multi-period production line scheduling

Abstract

An Experimental Investigation and Comparative Evaluation of Flowshop Scheduling Techniques

Ops Res.

Multi-product Scheduling in a Chemical Plant

Mgmt Sci.

Planning Tire Production

Mgmt Sci.

Scheduling a Multi-product Single Machine System

Opl Res. Q.

A Functional Heuristic Algorithm for the Flowshop Scheduling Problem

Opl Res. Q.

Multi-product Production Scheduling for Style Goods with Limited Capacity, Forecast Revisions and Terminal Delivery

Mgmt Sci.

A Goal Programming Model of Aggregate Production Planning

Swedish J. Econ.

The Scheduling of Continuous Flow Production: a Seperable Programming Approach

Opl Res. Q.

An Efficient Algorithm for Multi-item Scheduling

Ops Res.

Optimal Production Planning by a Gradient Technique and First Variations

Mgmt Sci.

Paper
A goal programming approach to multi-period production line scheduling