Heuristic Methods for the Multi-product Dynamic Lot Size Problem

Iyogun, Paul

doi:10.1057/jors.1991.169

Cited by 11 publications

(4 citation statements)

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“…Runtime issues with exact algorithms encouraged researchers to propose heuristical approaches not connected at all to exact approaches. Greedyadd (Federgruen and Tzur, 1994), greedy-drop, extended-Silver-Meal (Silver, 1973), general-partperiod-balancing (Iyogun, 1991) and many more are such heuristics.…”

Section: Solution Methodsmentioning

confidence: 99%

Dynamic lot size MIPs for multiple products and ELSPs with shortages, capacity and changeover limits

Garn

2020

Preprint

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Scheduling multiple products with limited resources and varying demands remain a critical challenge for many industries. This work presents mixed integer programs (MIPs) that solve the Economic Lot Sizing Problem (ELSP) and other Dynamic Lot-Sizing (DLS) models with multiple items. DLS systems are classified, extended and formulated as MIPs. Especially, logical constraints are a key ingredient in succeeding in this endeavour. They were used to formulate the setup/changeover of items in the production line. Minimising the holding, shortage and setup costs is the primary objective for ELSPs. This is achieved by finding an optimal production schedule taking into account the limited manufacturing capacity. Case studies for a production plants are used to demonstrate the functionality of the MIPs. Optimal DLS and ELSP solutions are given for a set of test-instances. Insights into the runtime and solution quality are given.

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Section: Solution Methodsmentioning

confidence: 99%

Dynamic lot size MIPs for multiple products and ELSPs with shortages, capacity and changeover limits

Garn

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…This is because these heuristics don't employ the pull order improvement mechanism in their steps. As mentioned in Iyogun (1991) , we could observe that GSM 2 performs better than GSM 1 because of the change made in the pull order mechanism. This is the first comprehensive comparison of all 3 variants of cost covering heuristic against a benchmark (DH), as in the paper by Joneja (1990) such a comparison was done only with a small set of problems.…”

Section: Problem Parametersmentioning

confidence: 65%

“…The part period balancing heuristic introduced by De Matties and Mendoza (1968) was extended by Iyogun (1991). The single item version of the heuristic calculates the accumulated holding cost for periods t, t+1, ..., t+l for meeting demands in these periods with an order from period t. If the earliest period at which accumulated holding cost exceeds the setup cost is at t + l, then an order is placed at t + l.…”

Section: Generalised Part Period Balancing Heuristic Variants 1 and 2)mentioning

confidence: 99%

“…The first extension known as Generalised silver meal heuristic -variant 1 (GSM1) was introduced in ATKINS and IYOGUN (1988). The second variant known as Generalised Silver meal heuristic -variant 2 (GSM2) was introduced in Iyogun (1991). We studied the 2 variants in the paper which were extensions of the heuristic originally introduced in Silver (1973).…”

Section: Generalised Silver Meal Heuristic -Variant 1 Andmentioning

confidence: 99%

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