Activities per year
Abstract
In a single item dynamic lotsizing problem, we are given a time horizon and demand for a single item in every time period. The problem seeks a solution that determines how much to produce and carry at each time period, so that we will incur the least amount of production and inventory cost. When the remanufacturing option is included, the input comprises of number of returned products at each time period that can be potentially remanufactured to satisfy the demands, where remanufacturing and inventory costs are applicable. For this problem, we first show that it cannot have a fully polynomial time approximation scheme (FPTAS). We then provide a pseudopolynomial algorithm to solve the problem and show how this algorithm can be adapted to solve it in polynomial time, when we make certain realistic assumptions on the cost structure. We finally give a computational study for the capacitated version of the problem and provide some valid inequalities and computational results that indicate that they significantly improve the lower bound for a certain class of instances.
Original language  English 

Title of host publication  Machine Learning, Optimization, and Big Data 
Subtitle of host publication  Second International Workshop, MOD 2016, Volterra, Italy, August 2629, 2016, Revised Selected Papers 
Editors  Panos M. Pardalos, Piero Conca, Giovanni Giuffrida, Giuseppe Nicosia 
Place of Publication  Cham, Switzerland 
Publisher  Springer 
Pages  132143 
Number of pages  12 
ISBN (Print)  9783319514680, 9783319514697 
DOIs  
Publication status  Published  25 Dec 2016 
Keywords
 lotsizing problem
 production cost
 inventory cost
 polynomial time
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Activities
 1 Organiser of major conference

Second International Workshop Machine Learning, Optimization and Big Data
Ashwin Arulselvan (Member of programme committee)
2016 → …Activity: Participating in or organising an event types › Organiser of major conference