We study the following lot-sizing models that recently appeared in the literature: a lot-sizing model with a remanufacturing option, a lot-sizing model with production time windows, and a lot-sizing model with cumulative capacities. We show the equivalence of these models with a classical model:...

Emphasis on effective demand management is becoming increasingly recognized as an important factor in operations performance. Operations models that account for supply costs and constraints as well as a supplier's ability to in°uence demand characteristics can lead to an improved match...

We address the dynamic lot sizing problem for systems with product returns. The demand and return amounts are deterministic over the finite planning horizon. Demands can be satisfied by manufactured/procured new items, but also by remanufactured returned items. The objective is to determine...

In this paper we analyze the worst case performance of heuristics for the classical economic lot-sizing problem with time-invariant cost parameters. We consider a general class of on-line heuristics that is often applied in a rolling horizon environment. We develop a procedure to systematically...

In this paper we investigate the complexity of the economic lot-sizing problem with remanufacturing (ELSR) options. Whereas in the classical economic lot-sizing problem demand can only be satisfied by production, in the ELSR problem demand can also be satisfied by remanufacturing returned items....

This paper considers a dynamic lot-sizing problem with storage capacity limitation in which backlogging is allowed. For general concave production and inventory costs, we present an O(T2) dynamic programming algorithm where ï”is the length of the planning horizon. Furthermore, for...

Experts often add domain knowledge to model-based forecasts while aiming to reduce forecast errors. Indeed, there is some empirical evidence that expert-adjusted forecasts improve forecast quality. However, surprisingly little is known about what experts actually do. Based on a large and...

This paper conjectures that the behaviour of experts who adjust statistical-model-based forecasts obeys the Law of Small Numbers [LSN]. To put this hypothesis to an empirical test, I propose a simple but effective methodology. It is applied to a database containing information on many experts...

The brand choice problem in marketing has recently been addressed with methods from computational intelligence such as neural networks. Another class of methods from computational intelligence, the so-called ensemble methods such as boosting and stacking have never been applied to the brand...

In this paper we give a short novel proof of the well-known Lagrange multiplier rule, discuss the sources of the power of this rule and consider several applications of this rule. The new proof does not use the implicit function theorem and combines the advantages of two of the most well-known...