English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper approaches the integrated lot sizing and scheduling problem(ILSSP), in which non-identical machines work in parallel with non-triangularsequence-dependent setup costs and times, setup carry-over and capacitylimitation. The aim of the studied ILSSP, here called ILSSP-NT on parallelmachines, is to determine a production planning and tasks sequencing that meetperiod demands without delay and in such a way that the total costs ofproduction, machine setup and inventory are minimized. The dearth of literatureon the ILSSP-NT, despite the increasing amount of applications in theindustrial sector, mainly in the food processing industry, motivated us toconduct this study. In this paper, we propose efficient methods to solve theILSSP-NT on parallel machines. The methods virtually consist in thehybridization of the relax-and-fix and fix-and-optimize methods with thepath-relinking and kernel search heuristics. To assess how well the heuristicssolve the ILSSP-NT on parallel machines, we compared their results with thoseof the CPLEX solver with a fixed CPU time limit. The proposed matheuristicssignificantly outperformed CPLEX in most of the tested instances.

Hybrid matheuristics to solve the integrated lot sizing and scheduling problem on parallel machines with sequence-dependent and non-triangular setup