Suchergebnisse

In a multi‐item environment with a joint set‐up cost structure considerable savings may be realised by co‐ordinating the replenishments. This article presents a unified survey of the inventory control literature designed to capture the models that fit in this frame. In general these models are complex and require a great deal of computational effort to obtain an exact solution. The literature relies mainly on heuristic procedures.

AbstractThis article presents a branch and bound method for solving the problem of minimizing a separable concave function over a convex polyhedral set where the variables are restricted to be integer valued. Computational results are reported.

Surveys multiple‐stage production planning literature to reveal that this sizeable body of research is largely inspired by single‐item production planning. Suggests several promising research opportunities, including the possible development of scheduling techniques not derived from older, single‐item procedures. Highlights the need for further comparative testing between existing "improved" techniques, as well as the wealth of work yet to be done in multiple‐stage production planning with limited resources and possible extensions to supply‐chain management.

A survey of project scheduling problems since 1973 limited to work
done specifically in the project scheduling area (although several
techniques developed for assembly line balancing and job‐shop scheduling
can be applicable to project scheduling): the survey includes the work
done on fundamental problems such as the resource‐constrained project
scheduling problem (RCPSP); time/cost trade‐off problem (TCTP); and
payment scheduling problem (PSP). Also discusses some recent research
that integrates RCPSP with either TCTP or PSP, and PSP with TCTP. In
spite of their practical relevance, very little work has been done on
these combined problems to date. The future of the project scheduling
literature appears to be developing in the direction of combining the
fundamental problems and developing efficient exact and heuristic
methods for the resulting problems.