On Modeling the Disassembly Lot Sizing Problem

Tevhide Altekin

Disassembly plays a central role in the circular economy, with studies estimating that effective remanufacturing and recycling can recapture up to 80% of a product's residual material value. Motivated by its practical significance, this paper studies the disassembly lot sizing (DLS) problem. The DLS problem involves determining the timing and quantity of cores to disassemble over a finite planning horizon so as to satisfy the demand for their recovered parts while minimizing total cost. Disassembly in any period requires a setup, incurring a setup cost, and each core disassembled incurs a disassembly cost. We assume complete disassembly; therefore, each core disassembly releases all parts specified in the bill of materials, each in proportion to its yield, i.e., the number of units of that part obtained from disassembling a single core. The demand for each part in each period is known over the planning horizon. Parts obtained in a given period can be used immediately to meet current demand or inventoried for future periods, with holding costs incurred for any parts remaining in inventory at the end of each period. The total cost consists of the setup, disassembly, and inventory holding costs. We study the DLS problem under both stationary and nonstationary cost parameters. Drawing on the well-established theory of the classical lot sizing problem (in particular, zero inventory property), to characterize and compare, we consider two alternative mixed-integer formulations and investigate the linear programming relaxation bounds for both uncapacitated and capacitated DLS problems. We also demonstrate the effectiveness of the proposed valid inequalities. This is joint work with Meltem Denizel (Ivy College of Business, Iowa State University) and Z. Pelin Bayındır (Department of Industrial Engineering, Middle East Technical University).

Short Bio

F. Tevhide Altekin is a faculty member at Sabancı Business School, Sabancı University. She received her B.S., M.S. and Ph.D. degrees in Industrial Engineering from Middle East Technical University. Her main research focuses on production planning problems in additive manufacturing, assembly and disassembly line design, closed loop supply chain management and design of after-sales networks. She teaches Ph.D., PMBA, MBA and undergraduate-level courses in operations and supply chain management, digital operations and supply chain management, and business analytics. She is the recipient of Sabancı University teaching awards in 2011 and 2024.

Venue

Friday, May 8, 2026, 4.00 pm

IE Building, Halim Doğrusöz Auditorium (IE 03)