Multiple-facility loading under capacity-based economies of scope

Multiple-facility loading (MFL) involves the allocation of products among a set of finite-capacity facilities. Applications of MFL arise naturally in a variety of production scheduling environments. MFL models typically assume that capacity is consumed as a linear function of products assigned to a facility. Product similarities and differences, however, result in capacity-based economies or diseconomies of scope, and thus the effective capacity of the facility is often a (nonlinear) function of the set of tasks assigned to the facility. This article addresses the multiple-facility loading problem under capacity-based economies (and diseconomies) of scope (MFLS). We formulate MFLS as a nonlinear 0–1 mixed-integer programming problem, and we discuss some useful properties. MFLS generalizes many well-known combinatorial optimization problems, such as the capacitated facility location problem and the generalized assignment problem. We also define a tabu-search heuristic and a branch-and-bound algorithm for MFLS. The tabu-search heuristic alternates between two search phases, a regional search and a diversification search, and offers a novel approach to solution diversification. We also report computational experience with the procedures. In addition to demonstrating MFLS problem tractability, the computational results indicate that the heuristic is an effective tool for obtaining high-quality solutions to MFLS. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 229–256, 1997     

Scheduling economic lot sizes in deteriorating production systems

The paper considers the economic lot scheduling problem (ELSP) where production facility is assumed to deteriorate, owing to aging, with an increasing failure rate. The time to shift from an “in‐control” state to an “out‐of‐control” state is assumed to be normally distributed. The system is scheduled to be inspected at the end of each production lot. If the process is found to be in an “out‐of‐control” state, then corrective maintenance is performed to restore it to an “in‐control” state before the start of the next production run. Otherwise, preventive maintenance is carried out to enhance system reliability. The ELSP is formulated under the capacity constraint taking into account the quality related cost due to possible production of non‐conforming items, process inspection, and maintenance costs. In order to find a feasible production schedule, both the common cycle and time‐varying lot sizes approaches are utilized. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 650–661, 2003     

On nash subsets of bimatrix games

This work considers a class of bimatrix games to which some well-known structure theorems of 0-sum matrix games can be made to generalize. It is additionally shown how to construct such games and how to generate the equilibrium points defining a given game as a member of that class.     

On nash subsets and mobility chains in bimatrix games

This work is concerned with constructing, analyzing, and finding “mobility chains” for bimatrix games, sequences of equilibrium points along which it is possible for the two players to progress, one equilibrium point at a time, to an equilibrium point that is preferred by both players. The relationship between mobility chains and Nash subsets is established, and some properties of maximal Nash subsets are proved.     

Finite statistical games and linear programming

The dual linear programs associated with finite statistical games are investigated and their optimal solutions are interpreted. The usual statistical game is generalized to a two-sided (inference) game and its possible application as a tactical model is discussed.     

A note on optimal inventory management under inflation

This paper develops a discounted-cost model that is similar to the classical economic order quantity model but includes inflation rates as parameters of the inventory system. A numerical problem is solved to illustrate the effects.     

AWGN信道下线性分组码的差错概率下界分析

提出了一种线性分组码的最大似然译码(ML-decoding)差错概率下界的计算方法。差错概率的下界优化实质上是对联合事件概率下界的优化,算法结合改进的Dawson-Sankoff界的优化准则,提出了AWGN信道下线性分组码差错冗余事件的判决准则,得到了误码率下界的计算表达式。该表达式只依赖码字的Hamming重量分布与信噪比,较之类deCaens界与类KAT界,本算法得到的下界更紧,计算量更低。针对LDPC等线性分组码的数值结果证明了算法的优越性能。