Coordination of Outsourced Operations at a Third-Party Facility Subject to Booking, Overtime, and Tardiness Costs

We consider an outsourcing problem where a group of manufacturers outsource jobs to a single third party who owns a specialized facility needed to process these jobs. The third party announces the time slots available on her facility, and the associated prices. Manufacturers reserve, on a first-come-first-book basis, time slots that they desire to utilize. Booking of overtime is possible, at a higher cost. A job completed after its due date incurs a tardiness cost. Each manufacturer books chunks of facility time and sequences his jobs over the time slots booked to minimize his booking, overtime, and tardiness costs. This model captures the main features of outsourcing operations in industries such as semiconductor manufacturing, biotechnology, and drug R&D. In current practice, the third party executes all outsourced jobs without performing optimization and coordination. We investigate the issue of the third party serving as a coordinator to create a win--win solution for all. We propose a model based on a cooperative game as follows: i Upon receiving the booking requests from the manufacturers, the third party derives an optimal solution if manufacturers cooperate, and computes the savings achieved. ii She devises a savings sharing scheme so that, in monetary terms, every manufacturer is better off to coordinate than to act independently or coalesce with a subgroup of manufacturers. iii For her work, the third party withholds a portion ρ of the booking revenue paid by the manufacturers for time slots that are released after coordination. We further design a truth-telling mechanism that can prevent any self-interested manufacturer from purposely reporting false job data to take advantage of the coordination scheme. Finally, we perform a computational experiment to assess the value of coordination to the various parties involved.

[1]  George L. Vairaktarakis,et al.  Coordination of Outsourced Operations to Minimize Weighted Flow Time and Capacity Booking Costs , 2009, Manuf. Serv. Oper. Manag..

[2]  Herbert Hamers,et al.  On games corresponding to sequencing situations with ready times , 1995, Math. Program..

[3]  Nicholas G. Hall,et al.  Capacity Allocation and Scheduling in Supply Chains , 2010, Oper. Res..

[4]  Herbert Hamers,et al.  On a New Class of Parallel Sequencing Situations and Related Games , 2002, Ann. Oper. Res..

[5]  George L. Vairaktarakis,et al.  A Cooperative Savings Game Approach to a Time Sensitive Capacity Allocation and Scheduling Problem , 2013, Decis. Sci..

[6]  Robert McNaughton,et al.  Scheduling with Deadlines and Loss Functions , 1959 .

[7]  John Holton,et al.  Manufacturing Outsourcing for Small and Mid-Size Companies , 2008 .

[8]  Martin P. Loeb,et al.  Incentives in a Divisionalized Firm , 1979 .

[9]  J. M. Moore An n Job, One Machine Sequencing Algorithm for Minimizing the Number of Late Jobs , 1968 .

[10]  Ross Dawson,et al.  Living Networks: Leading Your Company, Customers, and Partners in the Hyper-Connected Economy , 2002 .

[11]  Alessandro Agnetis,et al.  Scheduling Problems with Two Competing Agents , 2004, Oper. Res..

[12]  Chris N. Potts,et al.  Single Machine Scheduling to Minimize Total Weighted Late Work , 1995, INFORMS J. Comput..

[13]  Daniel Granot,et al.  A Note on the Room-Mates Problem and a Related Revenue Allocation Problem , 1984 .

[14]  Herbert Hamers,et al.  Job scheduling, cooperation, and control , 2006, Oper. Res. Lett..

[15]  Herbert Hamers,et al.  On the balancedness of multiple machine sequencing games , 1999, Eur. J. Oper. Res..

[16]  L. Shapley Cores of convex games , 1971 .

[17]  E. Lawler A “Pseudopolynomial” Algorithm for Sequencing Jobs to Minimize Total Tardiness , 1977 .

[18]  Wedad Elmaghraby,et al.  Supply Contract Competition and Sourcing Policies , 2000, Manuf. Serv. Oper. Manag..

[19]  George L. Vairaktarakis,et al.  Noncooperative Games for Subcontracting Operations , 2013, Manuf. Serv. Oper. Manag..

[20]  S. Tijs,et al.  Permutation games: Another class of totally balanced games , 1984 .

[21]  Stavros G. Kolliopoulos,et al.  Approximation algorithms for minimizing the total weighted tardiness on a single machine , 2006, Theor. Comput. Sci..

[22]  Herbert Hamers,et al.  Sequencing games : A survey , 2002 .

[23]  E. H. Clarke Multipart pricing of public goods , 1971 .

[24]  Theodore Groves,et al.  Incentives in Teams , 1973 .

[25]  Tolga Aydinliyim,et al.  Technical Memorandum Number 819 Centralization vs . Competition in Subcontracting Operations , 2007 .

[26]  Eran Hanany,et al.  Decentralization Cost in Scheduling: A Game-Theoretic Approach , 2007, Manuf. Serv. Oper. Manag..

[27]  Stef Tijs,et al.  Sequencing and Cooperation , 1994, Oper. Res..

[28]  Ruggiero Cavallo,et al.  Optimal decision-making with minimal waste: strategyproof redistribution of VCG payments , 2006, AAMAS '06.

[29]  Joseph Y.-T. Leung,et al.  Competitive Two-Agent Scheduling and Its Applications , 2010, Oper. Res..

[30]  Herbert Hamers,et al.  On the convexity of games corresponding to sequencing situations with due dates , 2002, Eur. J. Oper. Res..

[31]  Jerry R. Green,et al.  Characterization of Satisfactory Mechanisms for the Revelation of Preferences for Public Goods , 1977 .

[32]  Wenzhong Li,et al.  Solution of and bounding in a linearly constrained optimization problem with convex, polyhedral objective function , 1995, Math. Program..

[33]  Michael Pinedo,et al.  Scheduling: Theory, Algorithms, and Systems , 1994 .

[34]  Donald B. Gillies,et al.  3. Solutions to General Non-Zero-Sum Games , 1959 .