Asia-Pacific Journal of Operational Research

This research addresses a multi-item newsvendor problem with an equality resource constraint. We focus on retail industries with insufficient development power, where shelves must be filled with a variety of goods at the beginning of every period to make the selling space attractive. Technically, the total occupation volume of the goods must be adjusted to the shelf space. Using resource terminology, these elements correspond to resource consumption and resource capacity, respectively. Thus, we consider a constraint in which the total resource consumption is adjusted to a given resource capacity. We derive explicit solutions for several scenarios regarding resource capacity. These give important managerial implications that are helpful for both managers and front-line workers. We also consider two approaches for obtaining an approximate optimal solution for an arbitrary resource capacity, one of which can be implemented with ease in an ordering support system.

This paper presents a generalized stochastic Petri-net model for performance analysis and allocation optimization of a repair system with interchangeable inventory. A repair system with interchangeable-inventory is an important type of repair-service, which features components that are assembled circularly with interchangeable-component inventory. Despite improved efficiency, major difficulties in model formulation and performance analysis arise due to a complex fork/join structure and the presence of interchangeable-component inventory. In this study, by applying a generalized stochastic Petri-net to model the fork/join structure and interchangeable inventory, a system with one overhaul center and one interchangeable-component repair shop was defined in the Petri-net by places, transitions and tokens. A performance analysis with single and multiple parameters and simulation experiments was performed according to the real field data of high-speed railway locomotives overhaul. With appropriate weights on each portion of the system resources, the optimal design scenario for the allocation of a specific repair system was achieved to control the overall expenditure.

The conjugate gradient method is widely used in unconstrained optimization, especially for large-scale problems. Recently, Zhang et al. proposed a three-term PRP method (TTPRP) and a three-term HS method (TTHS), both of which can produce sufficient descent conditions. In this paper, the global convergence of the TTPRP and TTHS methods is studied, in which the line search procedure is replaced by a fixed formula of stepsize. This character is of significance when the line search is expensive in some particular applications. In addition, relevant computational results are also presented.

This paper researches the coordination models in the supply chain where there are uncertain two-echelon yields and random demand. We analyzed three contracts of revenue sharing (RS), overproduction risk sharing (OS), and combination of RS and OS (RO), and contrasted them with uncoordinated model. We studied the optimal order decision for downstream manufacturer and the optimal production decision for upstream manufacturer. Numerical examples were presented to illustrate the results. The study showed that the RS contract and OS sharing contract both have their advantages and disadvantages and the RO contract could benefit the whole supply chain best. We found out that the OS contract gives the upstream manufacturer incentive to produce more so as to maximize the profit value, but the upstream manufacturer may receive less as the price of overproduced part increases. We also found out that under most scenarios, the supply chain benefits from the yields and demand risks reduction and generates a higher profit. But sometimes in the OS contract the downstream manufacturer profit can increase as yields randomness increases. And, in the uncoordinated case and OS contract, the upstream manufacturer profit can increase as demand randomness increases.

The distribution of the "mixing time" or the "time to stationarity" in a discrete time irreducible Markov chain, starting in state i, can be defined as the number of trials to reach a state sampled from the stationary distribution of the Markov chain. Expressions for the probability generating function, and hence the probability distribution of the mixing time, starting in state i, are derived and special cases explored. This extends the results of the author regarding the expected time to mixing [Hunter, JJ (2006). Mixing times with applications to perturbed Markov chains. Linear Algebra and Its Applications, 417, 108–123] and the variance of the times to mixing, [Hunter, JJ (2008). Variances of first passage times in a Markov chain with applications to mixing times. Linear Algebra and Its Applications, 429, 1135–1162]. Some new results for the distribution of the recurrence and the first passage times in a general irreducible three-state Markov chain are also presented.

This paper presents a hybrid metaheuristic for solving the static dial-a-ride problem with heterogeneous vehicles and fixed costs. The hybridization combines a reactive greedy randomized adaptive search, used as outer scheme, with a tabu search heuristic in the local search phase. The algorithm is evaluated on well-known instances taken from the literature and on a set of randomly generated test problems, varying in the number of customers. Extensive computational results show the effectiveness of the hybrid approach in terms of trade-off between solution quality and computational time.

This paper estimates and compares efficiency performance of 32 commercial banks in Vietnam during 2001–2005, as well as identifies possible factors determining such efficiency performance. Efficiency is measured by a data envelopment analysis (DEA) model and super-efficiency measure through a slacks-based model (SBM) under the assumption of variable returns to scale (VRS). We find that there were a small number of efficient banks, and there would be room for these banks to improve their production efficiency. Moreover, in comparison with small banks, large banks do not guarantee high super efficiency scores. The results from a Tobit regression model provide such interesting findings as negative impact of state ownership, positive influence of bank size and market share, but no impact of labor quality.

In this paper, we consider the scheduling problem in which the jobs are first processed on a single machine and then delivered in batches by a single vehicle with limited capacity to the respective customers located at the vertices of a star-shaped network. The goal is to minimize the makespan. We present a 3/2-approximation algorithm for the identical job size case and a 2-approximation algorithm for the non-identical job sizes case.