The Production of Several Items in a Single Facility with Linearly Changing Demand Rates

Wagner, Bret; Davis, Darwin J.; Kher, Hemant V.

doi:10.1111/j.1540-5915.2002.tb01647.x

Cited by 26 publications

(17 citation statements)

References 14 publications

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“…Single machine scheduling environments actually occur in several practical operations (for a recent example in the chemical industry, see [1]). Also, the performance of many production systems is frequently determined by the quality of the schedules for a single bottleneck machine.…”

Section: Introductionmentioning

confidence: 99%

A genetic algorithm approach for the single machine scheduling problem with linear earliness and quadratic tardiness penalties

Valente

Gonçalves

2009

Computers & Operations Research

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In this paper, we consider the single machine scheduling problem with linear earliness and quadratic tardiness costs, and no machine idle time. We propose a genetic approach based on a random key alphabet. Several genetic algorithms based on this approach are presented. These versions differ on the generation of the initial population, as well as on the use of local search. The proposed procedures are compared with existing heuristics, as well as with optimal solutions for the smaller instance sizes. The computational results show that the performance of the proposed genetic approach is improved by the addition of a local search procedure, as well as by the insertion of simple heuristic solutions in the initial population. Indeed, the genetic versions that include either or both of these features not only provide significantly better results, but are also much faster. The genetic versions that use local search are clearly superior to the existing heuristics, and the improvement in performance over the best existing procedure increases with both the size and difficulty of the instances. These genetic procedures are also quite close to the optimum, and provided an optimal solution for most of the test instances. Scope and purposeThis paper considers a single machine scheduling problem with linear earliness and quadratic tardiness costs, and no machine idle time. Scheduling with early and tardy penalties has received considerable attention from the scheduling community, due to its practical importance. Indeed, early/tardy scheduling problems are compatible with the concepts of Just-in-Time production and supply chain management, which have been adopted by many organizations. Single machine scheduling environments actually occur in several practical applications. Also, the performance of many production systems is often determined by the schedules for a single bottleneck machine. Furthermore, the study of single machine problems frequently provides results that prove useful for more complex scheduling environments. The assumption that no machine idle time is allowed is also appropriate for many production settings. In fact, idle time should be avoided when the machine has limited capacity or high operating costs, and when starting a new production run involves high set-up costs or times. In this paper, we present several algorithms based on a genetic approach that uses a random key alphabet. The various versions of the genetic algorithm differ on the generation of the initial population, as well as on the use of local search. These procedures are compared with existing heuristics, as well as with optimal solutions for some instance sizes. The computational results show that inserting solutions generated by simple heuristics in the initial population, and using a local search procedure, enhances the performance of the proposed genetic approach. In fact, the addition of one or both of these features improves both the solution quality and the speed of the genetic algorithm. The genetic versions that apply local search c...

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Section: Introductionmentioning

confidence: 99%

A genetic algorithm approach for the single machine scheduling problem with linear earliness and quadratic tardiness penalties

Valente

Gonçalves

2009

Computers & Operations Research

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“…If demand could not support the higher price, then the decline in demand would create a natural phase‐out of the product. Considering dynamic changes in demand similar to Wagner et al (2002), but in a broader modeling context, would create a useful analysis and planning tool.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Inventory evaluation and product slate management in large‐scale continuous process industries

Cooke

Rohleder

2005

J of Ops Management

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Managing production and inventory for large-scale continuous processing plants is a key to success in the chemical process industry, particularly in the production of commodity polymers such as polyethylene and polypropylene. When setting up a production schedule, planners must consider the effects of off-grade production and production rate penalties, which are typically sequence-dependent as products are transitioned from one to another, as well as inventory holding costs and capacity constraints. We call this the continuous economic lot sizing and scheduling problem (CELSP) to distinguish it from closely related problems found in discrete part production industries. We present a formulation that addresses the particular aspects of the CELSP and apply the proposed mathematical modeling approach to several plants of a chemical processing company. This company was concerned with ensuring the plants were carrying proper amounts of inventory and with evaluating the number of products produced at each plant. Our results show actual overall inventory levels were close to the levels suggested by our model and therefore company plans for further inventory reductions would not be appropriate. However, the company should carefully consider the addition of new products to current plant product slates. Due to the effects of product transitions and inventory levels, even adding products with significant contribution margins may negatively affect the financial performance of the plant. #

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“…However, this scheduling environment does indeed occur in several activities (for a recent example, see Wagner, Davis, & Kher, 2002). Moreover, the performance of many production systems is quite often dictated by the quality of the schedules for a single bottleneck machine.…”

Section: Introductionmentioning

confidence: 99%

Dispatching heuristics for the single machine early/tardy scheduling problem with job-independent penalties

Valente

2007

Computers & Industrial Engineering

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In this paper, we consider the single machine earliness/tardiness scheduling problem with job-independent penalties, and no machine idle time. Several dispatching heuristics are proposed, and their performance is analysed on a wide range of instances. The heuristics include simple scheduling rules, as well as a procedure that takes advantage of the strengths of each of those rules. We also consider early/tardy dispatching procedures, and a heuristic method based on existing adjacent precedence conditions. An improvement procedure that can be used to improve the schedules generated by the heuristics is also proposed.The computational tests show that the best results are given by the early/tardy dispatching rules. These heuristics are also quite fast, and are capable of quickly solving even very large instances. The use of the improvement procedure is recommended, since it improves the solution quality, with little additional computational effort.

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The Production of Several Items in a Single Facility with Linearly Changing Demand Rates

Cited by 26 publications

References 14 publications

A genetic algorithm approach for the single machine scheduling problem with linear earliness and quadratic tardiness penalties

A genetic algorithm approach for the single machine scheduling problem with linear earliness and quadratic tardiness penalties

Inventory evaluation and product slate management in large‐scale continuous process industries

Dispatching heuristics for the single machine early/tardy scheduling problem with job-independent penalties

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