International Journal of Supply and Operations Management http://www.ijsom.com/ Wed, 15 Mar 2017 10:11:32 +0100 FeedCreator http://www.ijsom.com/ Feed provided by International Journal of Supply and Operations Management. Click to visit. http://www.ijsom.com/article_2671_500.html Material selection is a challenging issue in manufacturing processes while the inappropriate selected material may lead to fail the manufacturing process or end user experience especially in high-tech industries such as aircraft and shipping. Every material has different quantitative and qualitative criteria which should be considered simultaneously when assessing and selecting the right material. A weighted linear optimization method (WLOM) in the class of data envelopment analysis which exists in literature is adopted to address material selection problem while accounting for both qualitative and quantitative criteria. However, it is demonstrated the adopted WLOM method is not able to produce a full ranking vector for the material selection problems borrowed from the literature. Thus, an augmented common weight data envelopment analysis model (ACWDEA) is developed in this paper with the aim of eliminating deficiencies of WLOM model. The proposed ACWDEA is able to produce full ranking vector in decision making problems with less computational complexities in superior to the WLOM. Two material selection problems are solved and results are compared with WLOM and previous methods. Finally, the robustness and effectiveness of the proposed ACWDEA method are evaluated through Spearman’s correlation tests. Sun, 31 Jul 2016 19:30:00 +0100 http://www.ijsom.com/article_2697_0.html In this paper, we propose a sensitivity analysis for evaluating the effectiveness of recovery solutions in the case of disturbed rail operations. Indeed, when failures or breakdowns occur during daily service, new strategies have to be implemented so as to react appropriately and re-establish ordinary conditions as rapidly as possible. In this context, the use of rail simulation is vital: for each intervention strategy it provides the evaluation of interactions and performance analysis prior to actually implementing the corrective action. However, in most cases, simulation tasks are deterministic and fail to allow for the stochastic distribution of train performance and delays. Hence, the strategies adopted might not be robust enough to ensure effectiveness of the intervention. We therefore propose an off-line procedure for disruption management based on a microscopic and stochastic rail simulation which considers both service operation and travel demand. An application in the case of a real metro line in Naples (Italy) shows the benefits of the proposed approach in terms of service quality. Fri, 06 Jan 2017 20:30:00 +0100 http://www.ijsom.com/article_2672_500.html A supply chain is a set of facilities connected together in order to provide products to customers. The supply chain is subject to random failures caused by different factors which cause the unavailability of some sites. Given the current economic context, the management of these unavailabilities is becoming a strategic choice to ensure the desired reliability and availability levels of the different supply chain facilities. In this work, we treat two problems related to the field of supply chain, namely the design and unavailabilities management of logistics facilities. Specifically, we consider a stochastic distribution network with consideration of suppliers' selection, distribution centres location (DCs) decisions and DCs’ unavailabilities management. Two resolution approaches are proposed. The first approach called non-integrated consists on define the optimal supply chain structure using an optimization approach based on genetic algorithms (GA), then to simulate the supply chain performance with the presence of DCs failures. The second approach called integrated approach is to consider the design of the supply chain problem and unavailabilities management of DCs in the same model. Note that, we replace each unavailable DC by performing a reallocation using GA in the two approaches. The obtained results of the two approaches are detailed and compared showing their effectiveness. Sun, 31 Jul 2016 19:30:00 +0100 http://www.ijsom.com/article_2704_0.html This paper considers the multi-depot vehicle routing problem with time window in which each vehicle starts from a depot and there is no need to return to its primary depot after serving customers. The mathematical model which is developed by new approach aims to minimizing the transportation cost including the travelled distance, the latest and the earliest arrival time penalties. Furthermore, in order to reduce the problem searching space, a novel GA clustering method is developed. Finally, Experiments are run on number problems of varying depots and time window, and customer sizes. The method is compared to two other clustering techniques, fuzzy C means (FCM) and K-means algorithm. Experimental results show the robustness and effectiveness of the proposed algorithm. Sat, 25 Feb 2017 20:30:00 +0100 http://www.ijsom.com/article_2684_500.html A fundamental problem is the use of DEA in multistep or multilevel processes such as supply chain, lack of attention to processes’ internal communications in a way that the recent studies on DEA in the context of serial processes have focused on closed systems that the outputs of one level become the inputs of the next level and none of the inputs enter the mediator process. The present study aimed to examine the general dimensions of an open multilevel process. Here, some of the data such as inputs and outputs are supposed to leave the system while other outputs turn into the inputs of the next level. The new inputs can enter the next level as well. We expand this mode for network structures. The overall performance of such a structure is considered as a weighted average of sectors’ performance or distinct steps. Therefore, this suggested model in this study, not only provides the possibility to evaluate the performance of the entire network, but creates the performance analysis for each of the sub-processes. On the other hand, considering the data with undesirable structure leads to more correct performance estimation. In the real world, all productive processes do not comprise desirable factors. Therefore, presenting a structure that is capable of taking into account the undesirable structure is of crucial importance. In this study, a new model in the DEA by network structure is offered that can analyze the performance considering undesirable factors. Sun, 31 Jul 2016 19:30:00 +0100 http://www.ijsom.com/article_2705_0.html In this paper, we study the problem of integrated capacitated hub location problem and seat inventory control considering concept and techniques of revenue management. We consider an airline company maximizes its revenue by utilizing the best network topology and providing proper booking limits for all itineraries and fare classes. The transportation system arises in the form of a star/star network and includes both hub-stop and non-stop flights. This problem is formulated as a two-stage stochastic integer program with mixed-integer recourse. We solve various instances carried out from the Turkish network data set. Due to the NP-hardness of the problem, we propose a hybrid optimization method, consisting of an evolutionary algorithm based on genetic algorithm and exact solution. The quality of the solutions found by the proposed meta-heuristic is compared with the original version of GA and the mathematical programming model. The results obtained by the proposed model imply that integrating hub location and seat inventory control problem would help to increase the total revenue of airline companies. Also, in the case of serving non-stop flights, the model can provide more profit by employing less number of hubs. Sat, 25 Feb 2017 20:30:00 +0100 http://www.ijsom.com/article_2685_500.html In the previous decade, fossil energy resources shortage and environmental challenges such as air and water pollution, global warming, and greenhouse-gas emissions, etc. have increased environmental concerns considerably. Since, one of the most practical and useful solutions to decrease environmental pollutants is to deploy green purchasing and clean energies by organizations or even governments. Thus, the construction of renewable-energy power plants and, consequently, the green supplier selection for these plants’ equipment has become more important. With this respect, this article presents a novel approach to assess and select green suppliers of a solar power plant. The proposed approach integrates Fuzzy Analytic Hierarchy Process and VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje) methodologies. The results demonstrate the efficiency of the proposed approach as a practical tool to assist managers and CEOs (Chief Executive Officers) of electric power industry in assessing suppliers of solar power plant’s equipment. Sun, 31 Jul 2016 19:30:00 +0100 http://www.ijsom.com/article_2707_0.html This paper presents the formulation and solution of the Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem. The focus of the proposed method is not on finding a single optimal solution, instead on presenting multiple feasible solutions, with cost and duration information to the project manager. The motivation for developing such an approach is due in part to practical situations where the definition of optimal changes on a regular basis. The proposed approach empowers the project manager to determine what is optimal, on a given day, under the current constraints, such as, change of priorities, lack of skilled worker. The proposed method utilizes a simulation approach to determine feasible solutions, under the current constraints. Resources can be non-consumable, consumable, or doubly constrained. The paper also presents a real-life case study dealing with scheduling of ship repair activities. Sat, 11 Mar 2017 20:30:00 +0100 http://www.ijsom.com/article_2686_500.html AbstractThis work investigates the effect of different inventory policies of a supply chain model using the system dynamics approach which belongs to the class of Vendor Managed Inventory (VMI), automatic pipeline, inventory and order based production control systems (VMI-APIOBPCS). This work helps management to investigate the effect of different policies such as adding the VMI system or third party logistic (TPL) on the whole cost of the supply chain. To this end, this work applies system dynamics in supply chain with two supplier and one retail channel which consists of VMI system. Moreover, this work studies the performance of the proposed model via three metrics: Bullwhip effect; satisfaction of the end-customer; the amount of the whole inventory of chain. Sun, 31 Jul 2016 19:30:00 +0100 http://www.ijsom.com/article_2692_500.html We address in this paper a periodic petroleum station replenishment problem (PPSRP) that aims to plan the delivery of petroleum products to a set of geographically dispatched stations. It is assumed that each station is characterized by its weekly demand and by its frequency of service. The main objective of the delivery process is to minimize the total travelled distance by the vailable trucks over an extended planning horizon. The problem configuration is described through a set of trucks with several compartments each and a set of stations with demands and prefixed delivery frequencies. Given such input data, the minimization of the total distance is subject to assignment and routing constraints that express the capacity limitations of each truck's compartment in terms of the frequency and the pathways' restrictions. In this paper, we develop and solve the full space mathematical formulation for the PPSRP with application to the Omani context. Our ultimate aim is to include such a model into an integrated framework having the objective of advising petroleum distribution companies on how to prepare bids in case of participation in combinatorial auctions of the transportation procurement. Sun, 31 Jul 2016 19:30:00 +0100 http://www.ijsom.com/article_2696_500.html In most manufacturing processes, each product may contain a variety of quality characteristics which are of the interest to be optimized simultaneously through determination of the optimum setting of controllable factors. Although, classic experimental design presents some solutions for this regard, in a fuzzy environment, and in cases where the response data follow non-normal distributions, the available methods do not apply any more. In this paper, a general framework is introduced in which NORTA inverse transformation technique and fuzzy goal programming are used to deal with non-normality distribution of the response data and the fuzziness of response targets respectively. Moreover, the presented framework uses a simulation approach to investigate the effectiveness of the determined setting of controllable factors obtained from statistical analysis, for optimization of sink mark index, deflection rate and volumetric shrinkage in plastic molding manufacturing processes. The accuracy of the proposed method is verified through a real case study. Sun, 31 Jul 2016 19:30:00 +0100