Meltem Denizel

Multiperiod Remanufacturing Planning With Uncertain Quality of Inputs

In this paper, we consider production planning when inputs have different and uncertain quality levels, and there are capacity constraints. This situation is typical of most remanufacturing environments, where inputs are product returns (also called cores). Production (remanufacturing) cost increases as the quality level decreases, and any unused cores may be salvaged at a value that increases with their quality level. Decision variables include, for each period and under a certain probabilistic scenario, the amount of cores to grade, the amount to remanufacture for each quality level, and the amount of inventory to carry over for future periods for ungraded cores, graded cores, and finished remanufactured products. Our model is grounded with data collected at a major original equipment manufacturer that also remanufactures. We formulate the problem as a stochastic program; although it is a large linear program, it can be solved easily using Cplex. We provide a numeric study to generate insights into the nature of the solution.

LAGRANGEAN RELAXATION BASED HEURISTICS FOR LOT SIZING WITH SETUP TIMES

We consider a lot sizing problem with setup times where the objective is to minimize the total inventory carrying cost only. The demand is dynamic over time and there is a single resource of limited capacity. We show that the approaches implemented in the literature for more general versions of the problem do not perform well in this case. We examine the Lagrangean relaxation (LR) of demand constraints in a strong reformulation of the problem. We then design a primal heuristic to generate upper bounds and combine it with the LR problem within a subgradient optimization procedure. We also develop a simple branch and bound heuristic to solve the problem. Computational results on test problems taken from the literature show that our relaxation procedure produces consistently better solutions than the previously developed heuristics in the literature.

Equivalence of the LP relaxations of two strong formulations for the capacitated lot-sizing problem with setup times

The multi-item Capacitated Lot-Sizing Problem (CLSP) has been widely studied in the literature due to its relevance to practice, such as its application in constructing a master production schedule. The problem becomes more realistic with the incorporation of setup times since they may use up significant amounts of the available resource capacity. In this paper, we present a proof to show the linear equivalence of the Shortest Path (SP) formulation and the Transportation Problem (TP) formulation for CLSP with setup costs and times. Our proof is based on a linear transformation from TP to SP and vice versa. In our proof, we explicitly consider the case when there is no demand for an item in a period, a case that is frequently observed in the real world and in test problems in the literature. The equivalence result in this paper has an impact on the choice of model formulation and the development of solution procedures.

Recovery decisions of a producer in a legislative disposal fee environment

The main objectives of the environmental legislation originating from extended producer responsibility (EPR) principle are to lead producers to undertake recovery initiatives for their end-of-use products and to promote environmentally desirable product design. It is still controversial whether current implementations of EPR principle are effective in attaining these objectives. This study seeks to answer the following questions: (1) What is the impact of EPR legislation on the product recovery decisions of producers? (2) How do the redesign opportunities (i.e., design for disassembly) affect the willingness of producers for product recovery? (3) How do the investment needs to start recovery practices and the reluctance of producers to allocate sufficient funds for this purpose affect the optimal recovery decisions? We use stylized economic models to represent the implementation in practice and solving our models we obtain closed form and numerical solutions that help us to see the impact of various parameters on the optimal decisions of a producer. Our findings indicate that redesign opportunities encourage producers for more recovery, however the reluctance of producers to cover the initial investments may substantially reduce the effectiveness of the legislation and the recovery amounts.

On alternative mixed integer programming formulations and LP-based heuristics for lot-sizing with setup times

We address the multi-item, capacitated lot-sizing problem (CLSP) encountered in environments where demand is dynamic and to be met on time. Items compete for a limited capacity resource, which requires a setup for each lot of items to be produced causing unproductive time but no direct costs. The problem belongs to a class of problems that are difficult to solve. Even the feasibility problem becomes combinatorial when setup times are considered. This difficulty in reaching optimality and the practical relevance of CLSP make it important to design and analyse heuristics to find good solutions that can be implemented in practice. We consider certain mixed integer programming formulations of the problem and develop heuristics including a curtailed branch and bound, for rounding the setup variables in the LP solution of the tighter formulations. We report our computational results for a class of instances taken from literature.

Drift or Shift? Continuity, Change, and International Variation in Knowledge Production in OR/MS

With the aim of contributing to the debate around OR/MS as a discipline, this study provides a historical comparative investigation of publicly available knowledge production in the field. The empirical investigation is based on a content analysis of 300 randomly selected articles from six major journals in the field. We have found: (1) since the late 1950s to the present day there has been no significant change in the types of published research in OR/MS in North America; (2) from the late 1950s to the present day, there have been significant differences in types of published research in OR/MS internationally. The imputed imbalance between theory and applications in published work had already occurred in the early stages of the development of OR/MS in North America and has since remained very much the same. Furthermore, research in the United Kingdom has been distinctly different from that dominant in North America and elsewhere. There are also indications that outside North America and the United Kingdom there is an emerging turn towards applications-oriented research. Over the last two or three decades there has been a significant increase overall in the share of articles published by academic authors.

Minimization of the Number of Tool Magazine Setups on Automated Machines: A Lagrangean Decomposition Approach

This paper addresses the parts-grouping problem that arises in automated manufacturing environments where appropriate cutting tools must be loaded on Computer Numerical Control (CNC) machines to process a variety of parts. Since tool-loading times may be considerably long and reduce available machine processing times, it is important to find a mutually exclusive grouping of parts such that the total number of tools required by each group does not exceed the tool-magazine capacity and the number of groups is minimized. We present an integer programming formulation of the problem and develop a lower bounding procedure using Lagrangean decomposition. We then introduce valid inequalities to improve the quality of the lower bounds obtained from the relaxed problem. Our solution procedure for the lower bounding problem requires only one set of Lagrange multipliers, which reduces the required computational effort significantly. We also modify the lower bound solution heuristically to find an upper bound. The lower and upper bounds are then incorporated in a branch-and-bound scheme to search for an optimal solution. Our computational comparisons with the best existing solution procedures from the literature show that our procedure performs better on average, and for the majority of test problems within the scope of our experiments.

Testing for convergence in bank efficiency: a cross-country analysis

This paper empirically investigates a possible convergence among the operational efficiency of financial institutions across countries. We explore (i) the relative performance of banking industries in two samples (European and global) over time, and (ii) whether banking industries are likely to attain the same level of efficiency in the long run as implied by international financial integration. We find that convergence in bank efficiency is incomplete and limited to European banking industries. Differing level of bank efficiencies across the globe may offer opportunities for international investors who would like to capitalize on such market imperfections. Our findings also have implications for policy makers who are concerned with the full integration and the stability of the global financial system.

Effective network formulations for lot sizing with backlogging in two-level serial supply chains

ABSTRACT This study considers the serial lot sizing problem with backlogging in two-level supply chains to determine when and how much to order at a warehouse and ship to a retailer over a T-period planning horizon so that the external known demand occurring at the retailer is satisfied and the total cost at all levels is minimized. In particular, the uncapacitated two-level serial lot sizing problem with backlogging and the two-level serial lot sizing problem with cargo capacity and backlogging are formulated using effective shortest-path network representations, which define the convex hull of their feasible solutions. These representations lead to efficient algorithms with O(T3) time for the uncapacitated problem and O(T6) time for the capacitated problem. Furthermore, a tight reformulation with O(T3) variables and O(T2) constraints (resp. O(T6) variables and O(T5) constraints) is proposed for the uncapacitated (resp. capacitated) problem.

Allocation of returned products among different recovery options through an opportunity cost¿based dynamic approach

In a make-to-order product recovery environment, we consider the allocation decision for returned products decision under stochastic demand of a firm with three options: refurbishing to resell, parts harvesting, and recycling. We formulate the problem as a multiperiod Markov decision process (MDP) and present a linear programming (LP) approximation that provides an upper bound on the optimal objective function value of the MDP model. We then present two solution approaches to the MDP using the LP solution: a static approach that uses the LP solution directly and a dynamic approach that adopts a revenue management perspective and employs bid-price controls technique where the LP is resolved after each demand arrival. We calculate the bid prices based on the shadow price interpretation of the dual variables for the inventory constraints and accept a demand if the marginal value is higher than the bid price. Since the need for solving the LP at each demand arrival requires a very efficient solution procedure, we present a transportation problem formulation of the LP via variable redefinitions and develop a one-pass optimal solution procedure for it. We carry out an extensive numerical analysis to compare the two approaches and find that the dynamic approach provides better performance in all of the tested scenarios. Furthermore, the solutions obtained are within 2% of the upper bound on the optimal objective function value of the MDP model.