A holding cost bound for the economic lot-sizing problem with time-invariant cost parameters

In this paper we derive a new structural property for an optimal solution of the economic lot-sizing problem with time-invariant cost parameters. We show that the total holding cost in an order interval of an optimal solution is bounded from above by a quantity proportional to the setup cost and the logarithm of the number of periods in the interval. Since we can also show that this bound is tight, this is in contrast to the optimality property of the economic order quantity (EOQ) model, where setup cost and holding cost are perfectly balanced. Furthermore, we show that this property can be used for the design of a new heuristic and that the result may be useful in worst case analysis.

A holding cost bound for the economic lot-sizing problem with time-invariant cost parameters

In this paper we derive a new structural property for an optimal solution of the economic lot-sizing problem with time-invariant cost parameters. We show that the total holding cost in an order interval of an optimal solution is bounded from above by a quantity proportional to the setup cost and the logarithm of the number of periods in the interval. Since we can also show that this bound is tight, this is in contrast to the optimality property of the economic order quantity (EOQ) model, where setup cost and holding cost are perfectly balanced. Furthermore, we show that this property can be used for the design of a new heuristic and that the result may be useful in worst case analysis

Mitigating the Cost of Anarchy in Supply Chain Systems

In a decentralized two-stage supply chain where a supplier serves a retailer who, in turn, serves end customers, operations decisions based on local incentives often lead to suboptimal system performance. Operating decisions based on local incentives may in such cases lead to a degree of system disorder or anarchy, wherein one party's decisions put the other party and/or the system at a disadvantage. While models and mechanisms for such problem classes have been considered in the literature, little work to date has considered such problems under nonstationary demands and fixed replenishment order costs. This paper models such two-stage problems as a class of Stackelberg games where the supplier announces a set of time-phased ordering costs to the retailer over a discrete time horizon of finite length, and the retailer then creates an order plan, which then serves as the supplier's demand. We provide metrics for characterizing the degree of efficiency (and anarchy) associated with a solution, and provide a set of easily understood and implemented mechanisms that can increase this efficiency and reduce the negative impacts of anarchic decisions

A note on "The Economic Lot Sizing Problem with Inventory Bounds"

In a recent paper, Liu (2008) considers the lot-sizing problem with lower and upper bounds on the inventory levels. He proposes an O(n^2) algorithm for the general problem, and an O(n) algorithm for the special case with non-speculative motives. We show that neither of the algorithms provides an optimal solution in general. Furthermore, we propose a fix for the former algorithm that maintains the O(n^2) complexity

Note on "An efficient approach for solving the lot-sizing problem with time-varying storage capacities"

In a recent paper Gutiérrez et al. (2008) show that the lot-sizing problem with inventory bounds can be solved in O(T log T) time. In this note we show that their algorithm does not lead to an optimal solution in general

The association of unplanned pregnancy with perinatal depression:A longitudinal cohort study

Perinatal depression is common, affecting approximately 7–13% of women. Studies have shown an association between unplanned pregnancy and perinatal depressive symptoms, but many used a cross-sectional design and limited postnatal follow-up. The current study investigated the association of unplanned pregnancy with perinatal depressive symptoms using a longitudinal cohort study that followed women from the first trimester until 12 months postpartum. Pregnant women (N = 1928) provided demographic and clinical data and information about pregnancy intention at the first trimester. Depressive symptoms were assessed during each trimester of pregnancy and five times postpartum using the Edinburgh Postnatal Depression Scale (EPDS) until 12 months postpartum. Mixed model analyses were used to investigate the association between an unplanned pregnancy and the level of depressive symptoms. Women with an unplanned pregnancy (N = 111, 5.8%) reported persistently higher levels of depressive symptoms during the entire perinatal period compared to women with a planned pregnancy, after adjustment for confounders (p < 0.001). However, the course of depressive symptom scores over time in women with an unplanned pregnancy was similar to that of women with a planned pregnancy. Lower age (p = 0.006), unemployment (p = 0.004), and history of depression (p < 0.001) were significantly associated with higher levels of perinatal depressive symptoms. An unplanned pregnancy may have a long-lasting negative impact on a woman’s perinatal mental health. Therefore, women with an unplanned pregnancy may benefit from systematic follow-up during the perinatal period with contingent mental health support

Economic lot-sizing with remanufacturing: complexity and efficient formulations

Within the framework of reverse logistics, the classic economic lot-sizing problem has been extended with a remanufacturing option. In this extended problem, known quantities of used products are returned from customers in each period. These returned products can be remanufactured, so that they are as good as new. Customer demand can then be fulfilled both from newly produced and remanufactured items. In each period, we can choose to set up a process to remanufacture returned products or produce new items. These processes can have separate or joint set-up costs. In this paper, we show that both variants are NP-hard. Furthermore, we propose and compare several alternative MIP formulations of both problems. Because ‘natural’ lot-sizing formulations provide weak lower bounds, we propose tighter formulations, namely shortest path formulations, a partial shortest path formulation and an adaptation of the (l, S, WW)-inequalities for the classic problem with Wagner-Whitin costs. We test their efficiency on a large number of test data sets and find that, for both problem variants, a (partial) shortest path type formulation performs better than the natural formulation, in terms of both the LP relaxation and MIP computation times. Moreover, this improvement can be substantial