International Journal of Supply and Operations Management
Volume:4 Issue: 1, Winter 2016

The school bus routing problem (SBRP) represents a variant of the well-known vehicle routing problem. The main goal of this study is to pick up students allocated to some bus stops and generate routes, including the selected stops, in order to carry students to school. In this paper, we have proposed a simple but effective metaheuristic approach that employs two features: first, it utilizes large neighborhood structures for a deeper exploration of the search space; second, the proposed heuristic executes an efficient transition between the feasible and infeasible portions of the search space. Exploration of the infeasible area is controlled by a dynamic penalty function to convert the unfeasible solution into a feasible one. Two metaheuristics, called N-ILS (a variant of the Nearest Neighbourhood with Iterated Local Search algorithm) and I-ILS (a variant of Insertion with Iterated Local Search algorithm) are proposed to solve SBRP. Our experimental procedure is based on the two data sets. The results show that N-ILS is able to obtain better solutions in shorter computing times. Additionally, N-ILS appears to be very competitive in comparison with the best existing metaheuristics suggested for SBRP

Nowadays, fiber-optic due to having greater bandwidth and being more efficient compared with other similar technologies, are counted as one the most important tools for data transfer. In this article, an integrated mathematical model for a three-level fiber-optic distribution network with consideration of simultaneous backbone and local access networks is presented in which the backbone network is a ring and the access networks has a star-star topology. The aim of the model is to determine the location of the central offices and splitters, how connections are made between central offices, and allocation of each demand node to a splitter or central office in a way that the wiring cost of fiber optical and concentrator installation are minimized. Moreover, each user’s desired bandwidth should be provided efficiently. Then, the proposed model is validated by GAMS software in small-sized problems, afterwards the model is solved by two meta-heuristic methods including differential evolution (DE) and genetic algorithm (GA) in large-scaled problems and the results of two algorithms are compared with respect to computational time and objective function obtained value. Finally, a sensitivity analysis is provided.Keyword: Fiber-optic, telecommunication network, hub-location, passive splitter, three-level network.

According to several studies, power and interdependence play a considerable role in understanding the buyer–supplier relationships, yet, empirical research is still limited. Also, the nature of the buyer-supplier relationship and managing them might vary based on the power position of buyers and suppliers. Few studies focused on the reason behind this interrelation and strong influence of power on the buyer-supplier relationships. Thus, the purpose of this study is to gain better understanding and try to identify how power position and buyer-supplier relationships are interrelated, and whether there are common determinants and/or characteristics behind this strong bond between the two concepts. Both transaction cost analysis theory and social exchange theory were integrated in building the argument. Regarding the methodology, qualitative exploratory research design was employed by using multiple-case study as the main research method, where three multinational Egyptian organizations were selected. Moreover, data was collected using individual in-depth interviews, and analyzed through coding and cross case analysis techniques. The results showed that there are common factors that influence both buyer-supplier relationship characteristics and power position attributes. And according, the findings helped in pointing out a new lens of discussing and investigating the bond between buyer-supplier relationships ad power in research.

In this paper, we consider the capacitated single allocation p-hub median problem generalized with fixed costs of opening facilities. The quadratic mathematical formulation of this problem is first adapted and then linearized. The typical approaches of linearization result in a high size complexity, i.e., having a large number of variables. To downsize the complexity, variables of the formulation are analyzed and some preprocessing approaches are defined. An estimated formulation is then developed to approximately solve large instances of the problem by commercial optimization solvers. The basic idea of this formulation is mapping the linearized formulation of the problem to a new formulation with fewer variables and a modified objective function. The efficacy of this formulation is shown by a computational study, where the estimated formulation is compared to a modified genetic algorithm from the literature. Results of computational experiments indicate that the estimated formulation is capable of generating good solutions within reasonable amount of time.

Recently, Kharazmi and Saadatinik (2016) introduced a new family of lifetime distributions called hyperbolic cosine – F (HCF) distribution. In the present paper, it is focused on a special case of HCF family with exponentiated exponential distribution as a baseline distribution (HCEE). Various properties of the proposed distribution including explicit expressions for the moments, quantiles, mode, moment generating function, failure rate function, mean residual lifetime, order statistics and expression of the entropy are derived. Estimating parameters of HCEE distribution are obtained by eight estimation methods maximum likelihood, Bayesian, maximum product of spacings, parametric bootstrap, non-parametric bootstrap, percentile, least-squares and weighted least-squares. A simulation study is conducted to examine the bias, mean square error of the maximum likelihood estimators. Finally, one real data set has been analyzed for illustrative purposes and it is observed that the proposed model fits better than Weibull, gamma and generalized exponential distributions.

In this paper, for the first time in the literature, we integrated production scheduling decisions and WIPs planning decisions in a distributed environment. We study the distributed and flexible job shop scheduling problem (DFJSP) which involves the scheduling of jobs (products) in a distributed manufacturing environment, under the assumption that the shop floor of each factory/cell is configured as a flexible job shop. It is also assumed that the work-in-process (WIP) parts can be bought from the market instead of manufacturing them in-house, and they also can be sold in the market instead of processing their remaining operations and selling the end products. Moreover, the processing times of the operations can be decreased by paying a cost. However, there are a lower limit and an upper limit for the processing time of each operation. We formulate this general problem as a mixed integer linear programming (MILP) model. A fast heuristic algorithm is also developed to obtain good solutions in very short time. The algorithm is tested on some problem instances in order to evaluate its performance. Computational results show that the proposed heuristic is a computationally efficient and practical approach.

This paper studies the uncapacitated P-hub center problem in a network under decentralized management assuming time as a fuzzy variable. In this network, transport companies act independently, each company makes its route choices according to its own criteria. In this model, time is presented by triangular fuzzy number and used to calculate the fraction of users that probably choose hub routes instead of direct routes. To solve the problem, two genetic algorithms are proposed. The computational results compared with LINGO indicate that the proposed algorithm solves large-scale instances within promising computational time and outperforms LINGO in terms of solution quality.