On the complexity of the economic lot-sizing problem with remanufacturing options

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. Although the ELSR problem can be solved efficiently for some special cases, we show that the problem is NP-hard in general, even under stationary cost parameters

The trade-off between costs and carbon emissions from economic lot-sizing decisions

Logistics decisions can have a significant impact on carbon emissions, a driver of global warming. We consider emissions reductions from better utilization of a given fleet of vehicles. We study an Economic Lot-Sizing setting in which a decision-maker determines the amount to be shipped in each period, and in which demand can fluctuate. Our paper assesses the trade-off between costs and carbon emissions. The emission parameters are based on a survey of results from empirical studies and on real-life considerations. In order to model the trade-off, we introduce a bi-objective lot-sizing model to find the Pareto optimal solutions with respect to costs and emissions. Our experiments show that it is often costly to reduce carbon emissions from the cost optimal solution, compared to carbon prices in the market. The cases in which carbon emissions can be reduced most cost-efficiently are those in which carbon emissions are large relative to costs, typically because costs are the results of past investments and can be considered sunk.</p

Startup activity and employment growth in regions

Based on a model, the report outlines the impact of business start-ups on employment growth in Great Britain. Covering the 1980-1998 span, the data used were compiled for 60 British regions. Specific emphasis is put on short-term and long-term effects of the number of start-ups on regional employment creation. Besides, the above correlation is examined for various periods. The findings reveal that - compared to the Eighties - the significance of the number of starters as regards employment growth has risen during the Nineties.

Four equivalent lot-sizing models

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: the lot-sizing model with inventory bounds

A note on a multi-period profit maximizing model for retail supply chain management

In this note we present an efficient exact algorithm to solve the joint pricing and inventory problem for which Bhattacharjee and Ramesh (2000) proposed two heuristics. Our algorithm appears to be superior also in terms of computation time. Furthermore, we point out several mistakes in the paper by Bhattacharjee and Ramesh

A Polynomial Time Algorithm for a Deterministic Joint Pricing and Inventory Model

In this paper we consider the uncapacitated economic lot-size model, where demand is a deterministic function of price. In the model a single price need to be set for all periods. The objective is to find an optimal price and ordering decisions simultaneously. In 1973 Kunreuther and Schrage proposed an heuristic algorithm to solve this problem. The contribution of our paper is twofold. First, we derive an exact algorithm to determine the optimal price and lot-sizing decisions. Moreover, we show that our algorithm boils down to solving a number of lot-sizing problems that is quadratic in the number of periods, i.e., the problem can be solved in polynomial time

A Polynomial Time Algorithm for a Deterministic Joint Pricing and Inventory Model

In this paper we consider the uncapacitated economic lot-size model, where demand is a deterministic function of price. In the model a single price need to be set for all periods. The objective is to find an optimal price and ordering decisions simultaneously. In 1973 Kunreuther and Schrage proposed an heuristic algorithm to solve this problem. The contribution of our paper is twofold. First, we derive an exact algorithm to determine the optimal price and lot-sizing decisions. Moreover, we show that our algorithm boils down to solving a number of lot-sizing problems that is quadratic in the number of periods, i.e., the problem can be solved in polynomial time

The Economic Lot-Sizing Problem: New Results and Extensions

Een manier waarop bedrijven kosten kunnen reduceren is efficiënte productieplanning. Het centrale thema in dit proefschrift is een klassiek productieplanningsprobleem: het economische lot-sizing (ELS) probleem. Het doel in dit probleem is om aan de gegeven vraag voor een eindige, discrete planningshorizon te voldoen en de totale setup-, productie- en voorraadkosten te minimaliseren. We bekijken zowel aspecten rondom het klassieke probleem als uitbreidingen van het probleem. Ten eerste onderzoeken we de verhouding tussen de voorraadkosten en de setupkosten in een optimale oplossing. Vervolgens voeren we een worst-case analyse uit op een brede klasse van on-line heuristieken. Omdat het klassieke probleem relatief eenvoudig is, bekijken we ook een aantal uitbreidingen. We zijn geïnteresseerd of er efficiënte algoritmen bestaan voor deze uitbreidingen. Eerst bekijken we een integraal model waarin de vaststelling van de verkoopprijs en het maken van het productieschema simultaan plaatsvindt. We beschouwen zowel een model met een constante prijs als een model met verschillende prijzen over de tijd. Verder breiden we het ELS model uit met een mogelijkheid tot herproductie. We veronderstellen dat er een gegeven hoeveelheid producten terugkomt van de klant in elke periode. Deze producten kunnen geherproduceerd worden om aan de vraag te voldoen (naast reguliere productie). We ontwikkelen algoritmen en leiden complexiteitsresultaten af voor twee varianten van het probleem. In de ene variant zijn er gezamenlijke setupkosten voor productie en herproductie (in het geval van een gezamenlijke productielijn) en in de andere variant zijn er aparte setupkosten (in het geval van afzonderlijke productielijnen).One way for firms to reduce cost is efficient production planning. The main theme in this thesis is a classical production planning problem: the economic lot-sizing (ELS) problem. The objective of this problem is to find a production plan that satisfies the given demand for a finite, discrete planning horizon, and minimizes the total setup, production and holding costs. We study aspects of the classical problem as well as extensions of this problem. In the first part of the thesis we consider the ELS model with time-invariant costWilco van den Heuvel (1979) obtained his master’s degree in Econometrics and Operations Research with honors from Erasmus University Rotterdam in 2002. In the same year he started with his PhD research. His main interests are in Operations Research and in particular in (extensions of) the classical economic lot-sizing problem. His research resulted in five papers published in Computers & Operations Research, European Jour- nal of Operational Research, International Journal of Production Research and Operations Research Letters. Finally, in 2005 he was awarded the Chorafas Prize, a prize to stimulate young researchers

Worst case analysis for a general class of on-line lot-sizing heuristics.

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 construct worst case instances for a fixed time horizon and use it to derive worst case problem instances for an infinite time horizon. Our analysis shows that any on-line heuristic has a worst case ratio of at least 2. Furthermore, we show how the results can be used to construct heuristics with optimal worst case performance for small model horizons

A Geometric Algorithm to solve the NI/G/NI/ND Capacitated Lot-Sizing Problem in O(T^2) Time

In this paper we consider the capacitated lot-sizing problem (CLSP) with linear costs. It is known that this problem is NP-hard, but there exist special cases that can be solved in polynomial time. We derive a backward algorithm, based on the forward algorithm by Chen et al. (1994), to solve the general CLSP. By adapting this backward algorithm, we arrive at a new O(T^2) algorithm for the CLSP with non-increasing setup cost, general holding cost, non-increasing production cost and non-decreasing capacities over time. Numerical tests show the superior performance of our algorithm compared to the algorithm proposed by Chung and Lin (1988). We also analyze why this is the case