This paper addresses scheduling a set of weighted jobs on a single machine in presence of release date for delivery in batches to customers or to other machines for further processing. The problem is a natural extension of minimizing the sum of weighted flow times by considering the possibility of delivering jobs in batches and introducing batch delivery costs. The classical problem is NP-hard and then the extended version of the problem is NP-hard. The objective function is that of minimizing the sum of weighted flow times and delivery costs. The extended problem arises in a real supply chain network by cooperation between two layers of chain. Structural properties of the problem are investigated and used to devise a branch-and-bound solution scheme. Computational experiments show the efficiency of suggested algorithm for solving instances up to 40 jobs.

One of the most important steps to build an appropriate business unit is to setup a suitable long-term strategy. A good strategy helps organization take better advantage of the existing resources and improve the performance of the firm. This paper presents a hybrid method consists of importance-performance analysis combined with fuzzy analytical hierarchy process to determine different operating strategies to increase the performance of a cement industry in Iran. The results indicate that being competitive is number one priority followed by fast delivery, quality product, dependability, cost of production and flexibility.

Customer service is increasingly being recognized as a source of competitive advantage. The keys to provide effective customer service are determining the customer needs, accurately, and meeting and exceeding the needs in a consistent manner. Companies should adapt a strategic, proactive focus on customer service based on understanding logistic processes and designing the logistics system to meet their needs. This paper proposes an approach based on the quality function deployment (QFD), for ranking strategic actions to improve logistics service. The paper addresses the issue of how to deploy the house of quality (HOQ) to effectively and efficiently improve logistics processes and thus customer satisfaction. For data collection, fuzzy logic is used to deal with the ill-defined nature of the qualitative linguistic judgments required in the proposed HOQ. The methodology has been tested by means of a real case application, which refers to an Iranian company operating in the manufacturing industry.

In response to increasing inflexible customer demands and to improve the competitive advantage, industrial organizations have to adopt strategies to achieve cost reduction, continual quality improvement, increased customer service and on-time delivery performance. Selection of the most suitable plant or facility layout design for an organization is one among the most important strategic issues to fulfill all these above-mentioned objectives. Nowadays, many industrial organizations have come to realize the importance of proper selection of the plant or facility layout design to survive in the global competitive market. Selecting the proper layout design from a given set of candidate alternatives is a difficult task, as many potential qualitative and quantitative criteria need to be considered. This paper proposes a Euclidean distance based approach (WEDBA) as a multiple attribute decision making method to deal with the complex plant or facility layout design problems of the industrial environment. Three examples are included to illustrate the approach.

The way orders are accepted or rejected is the most important factor in customer satisfaction and success of make-to-order systems. The incoming orders to such organizations have certain delivery date in which the customer expects the order to be fulfilled and delivered. In some cases, unexpectedly increased orders exceed the existing capacity for on time fulfillment. In addition to rejection of order, as a typical choice, other options like outsourcing and capacity expansion are available to compensate for capacity shortage and deliver incoming orders according to schedule. However, each of the proposed options is superior in one or more criteria and so selecting the best one is not simply possible. The main goal of this study is to provide managers with a comprehensive, systematic, and applicable approach to evaluate and select the best of the existing options. For this purpose, a model comprised of some multi-criteria techniques is delivered. Our proposed model is a blend of FAHP and FTOPSIS methods. In this model, FAHP is first used to determine the weight of criteria and then Fuzzy-TOPSIS (FTOPSIS) is employed to rank the options. Finally, the proposed model is applied on an actual case to assess and examine its efficiency.

Supply chain coordination as an effective tool plays an important role in improving supply chain performance. In this article, a two-level supply chain with one manufacturer and two retailers is considered. The order quantity that retailers are faced with depends on the amount of advertisements and both retailers compete with each other on advertising. The Stackelberg game is established between manufacturer and retailers such that the manufacturer and the retailers play the leader and the follower roles, respectively. First, the manufacturer determines the wholesale prices for retailers and instead, the retailers determine the order quantity and advertising level, simultaneously. The manufacturer produces one kind of product and delivers it to retailers before the beginning of selling season. Retailers can affect the order quantity regarding the demand dependency on advertising level through the incurred costs from the advertising. In this paper, we show that we can achieve the desirable supply chain coordination through using combined quantity discount and advertising cost sharing contracts. We also consider the win-win situation for all the members of the supply chain.

Quadratic assignment problem (QAP) has been considered as one of the most complicated problems. The problem is NP-Hard and the optimal solutions are not available for large-scale problems. This paper presents a hybrid method using tabu search and simulated annealing technique to solve QAP called TABUSA. Using some well-known problems from QAPLIB generated by Burkard et al. (1997) [Burkard, R. E., Karisch, S. E., & Rendl, F. (1997). QAPLIB–a quadratic assignment problem library. Journal of Global Optimization, 10(4), 391-403.], two methods of TABUSA and TS are both coded on MATLAB and they are compared in terms of relative percentage deviation (RPD) for all instances. The performance of the proposed method is examined against Tabu search and the preliminary results indicate that the hybrid method is capable of solving real-world problems, efficiently.

Evaluation of proper supplier for manufacturing organizations is one of the most challenging problems in real time manufacturing environment due to a wide variety of customer demands. It has become more and more complicated to meet the challenges of international competitiveness and as the decision makers need to assess a wide range of alternative suppliers based on a set of conflicting criteria. Thus, the main objective of supplier selection is to select highly potential supplier through which all the set goals regarding the purchasing and manufacturing activity can be achieved. Because of these reasons, supplier selection has got considerable attention by the academicians and researchers. This paper presents a combined multi-criteria decision making methodology for supplier evaluation for given industrial applications. The proposed methodology is based on a compromise ranking method combined with Grey Interval Numbers considering different cardinal and ordinal criteria and their relative importance. A ‘supplier selection index’ is also proposed to help evaluation and ranking the alternative suppliers. Two examples are illustrated to demonstrate the potentiality and applicability of the proposed method.

Since independence, India has been one of the few developing countries to invest extensively in both science and technical education. In India, technical education plays a pivotal role in human resource development while creating skilled manpower, increasing industrial productivity and enhancing the quality of life. If a technical institute means to be effective in developing learned and qualified engineers, then it would be useful to know the performance of that technical institution. However, measuring the performance of a technical institution has received very little attention because it is very difficult to measure its output. Thus, this paper focuses on assessing the performance of eight Indian Institutes of Technology (IITs) using a combined approach of data envelopment analysis (DEA) and technique of order preference by similarity to ideal solution (TOPSIS). In the first phase, DEA is applied to shortlist the efficient IITs having the desired characteristics from the stakeholders’ point of view, and TOPSIS method is then employed to rank those efficient IITs while also identifying the best performing IIT. It is observed that IIT Kharagpur outperforms all the considered IITs which exactly corroborates with the findings of the recently published surveys/reports.

In this paper, we study a supply chain problem where a whole seller/producer distributes goods among different retailers. Such problems are always faces with uncertainty with input data and we have to use various techniques to handle the uncertainty. The proposed model of this paper considers different input parameters such as demand, capacity and cost in trapezoid fuzzy forms and using two ranking methods, we handle the uncertainty. The results of the proposed model of this paper have been compared with the crisp and other existing fuzzy techniques using some randomly generated data. The preliminary results indicate that the proposed models of this paper provides better values for the objective function and do not increase the complexity of the resulted problem.