Integrating operations and marketing decisions using delayed differentiation of products and guaranteed delivery time under stochastic demand

In this research, we integrate the issues related to operations and marketing strategy of firms characterized by large product variety, short lead times, and demand variability in an assemble-to-order environment. The operations decisions are the inventory level of components and semi-finished goods, and configuration of semi-finished goods. The marketing decisions are the products price and a lead time guarantee which is uniform for all products. We develop an integrated mathematical model that captures trade-offs related to inventory of semi-finished goods, inventory of components, outsourcing costs, and customer demand based on guaranteed lead time and price.The mathematical model is a two-stage, stochastic, integer, and non-linear programming problem. In the first stage, prior to demand realization, the operation and marketing decisions are determined. In the second stage, inventory is allocated to meet the demand. The objective is to maximize the expected profit per-unit time. The computational results on the test problems provide managerial insights for firms faced with the conflicting needs of offering: (i) low prices, (ii) guaranteed and short lead time, and (iii) a large product variety by leveraging operations decisions.

[1]  David A. Collier,et al.  THE MEASUREMENT AND OPERATING BENEFITS OF COMPONENT PART COMMONALITY , 1981 .

[2]  D. Collier Aggregate Safety Stock Levels and Component Part Commonality , 1982 .

[3]  Hau L. Lee,et al.  Effective Inventory and Service Management Through Product and Process Redesign , 1996, Oper. Res..

[4]  Hau L. Lee,et al.  Xilinx Improves Its Semiconductor Supply Chain Using Product and Process Postponement , 2000, Interfaces.

[5]  B. Tabrizi,et al.  Defining next-generation products: an inside look. , 1997, Harvard business review.

[6]  P. S. Davis,et al.  A branch‐bound algorithm for the capacitated facilities location problem , 1969 .

[7]  Egon Balas,et al.  programming: Properties of the convex hull of feasible points * , 1998 .

[8]  V. Donk Make to stock or make to order: the decoupling point in the food processing industries , 2001 .

[9]  J. F. Benders Partitioning procedures for solving mixed-variables programming problems , 1962 .

[10]  Maqbool Dada,et al.  Pricing and the Newsvendor Problem: A Review with Extensions , 1999, Oper. Res..

[11]  Jing-Sheng Song,et al.  Price, delivery time guarantees and capacity selection , 1998, Eur. J. Oper. Res..

[12]  T. M. Whitin Inventory Control and Price Theory , 1955 .

[13]  Jayashankar M. Swaminathan,et al.  Demand and Production Management with Uniform Guaranteed Lead Time , 2005 .

[14]  P. França,et al.  Solving Stochastic Transportation-Location Problems by Generalized Benders Decomposition , 1982 .

[15]  Jayashankar M. Swaminathan,et al.  Managing broader product lines through delayed differentiation using vanilla boxes , 1998 .

[16]  Jeffrey D. Camm,et al.  Cutting Big M Down to Size , 1990 .

[17]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[18]  G. Pisano,et al.  MANUFACTURING STRATEGY: AT THE INTERSECTION OF TWO PARADIGM SHIFTS , 1996 .

[19]  Maria Elena Bruni,et al.  Solving Nonlinear Mixed Integer Stochastic Problems: a Global Perspective , 2006 .

[20]  A. M. Geoffrion,et al.  Multicommodity Distribution System Design by Benders Decomposition , 1974 .

[21]  George L. Nemhauser,et al.  Handbooks in operations research and management science , 1989 .

[22]  S. Kravanja,et al.  The multilevel MINLP optimization approach to structural synthesis: the simultaneous topology, material, standard and rounded dimension optimization , 2005, Adv. Eng. Softw..

[23]  John R. Birge,et al.  Introduction to Stochastic Programming , 1997 .

[24]  Roger J.-B. Wets,et al.  Stochastic Programming: Solution Techniques and Approximation Schemes , 1982, ISMP.

[25]  John E. Beasley,et al.  Improving benders decomposition using a genetic algorithm , 2009, Eur. J. Oper. Res..

[26]  U. Karmarkar Integrative Research in Marketing and Operations Management , 1996 .

[27]  C. Yano,et al.  Coordinated Pricing and Production/Procurement Decisions: A Review , 2005 .

[28]  Matteo Fischetti,et al.  Combinatorial Benders' Cuts for Mixed-Integer Linear Programming , 2006, Oper. Res..

[29]  K. R. Baker Safety stocks and component commonality , 1985 .

[30]  Ignacio E. Grossmann,et al.  An outer-approximation algorithm for a class of mixed-integer nonlinear programs , 1986, Math. Program..

[31]  John A. Tomlin,et al.  An integer programming approach to a class of combinatorial problems , 1972, Math. Program..

[32]  Nils Boysen,et al.  Jena Research Papers in Business and Economics A general solution framework for component commonality problems , 2008 .

[33]  Liming Liu,et al.  Pricing and Lead Time Decisions in Decentralized Supply Chains , 2007, Manag. Sci..

[34]  Michel Gendreau,et al.  Accelerating Benders Decomposition by Local Branching , 2009, INFORMS J. Comput..

[35]  J. Hooker,et al.  Logic-based Benders decomposition , 2003 .

[36]  David L. Woodruff,et al.  Production planning with load dependent lead times , 2005, 4OR.

[37]  Sebastian K. Fixson,et al.  Modularity and Commonality Research: Past Developments and Future Opportunities , 2007, Concurr. Eng. Res. Appl..

[38]  A. M. Geoffrion Generalized Benders decomposition , 1972 .

[39]  M. D. Devine,et al.  A Modified Benders' Partitioning Algorithm for Mixed Integer Programming , 1977 .

[40]  Reha Uzsoy,et al.  Incorporating manufacturing lead times in joint production-marketing models: A review and some future directions , 2008, Ann. Oper. Res..

[41]  R. Raman,et al.  Modelling and computational techniques for logic based integer programming , 1994 .

[42]  Thomas L. Magnanti,et al.  Accelerating Benders Decomposition: Algorithmic Enhancement and Model Selection Criteria , 1981, Oper. Res..

[43]  M. Laughton,et al.  Large-scale mixed integer programming: Benders-type heuristics , 1984 .

[44]  Steven J. Erlebacher,et al.  Lead-time setting, capacity utilization, and pricing decisions under lead-time dependent demand , 1998 .

[45]  Omprakash K. Gupta,et al.  Branch and Bound Experiments in Convex Nonlinear Integer Programming , 1985 .