International Journal of Supply and Operations Management
Volume:6 Issue: 3, Summer 2019

In this paper, a guaranteed service model (GSM) is considered in a general supply chain with the releasing of the service time constraint. For this purpose, a bi-objective model is developed containing minimization of both service time and the holding cost of safety stock. Also, in addition to considering the return of items from inside of the chain, the returns from outside of the chain are considered to carry out remanufacturing, refurbishing, and repairing processes. The model is solved in a real-world case of the electronic product supply chain and the Pareto solution set is obtained to show the changes in the holding cost of safety stock based on the maximum time for the different services offered to customers.

We describe the two-stage maximum flow network interdiction problem under endogenous stochastic interdiction. Our model consists of two agents playing a Stackelberg game. A smuggler who wishes to maximize the expected flow of some illegal commodities that can be transmitted between a source and a sink without being detected. On the other hand, an attacker tries to minimize the flow of drugs by installing some detectors or adding some security controls on critical arcs to increase the probability of detection. We consider a stochastic program under endogenous uncertainty in which the interdictor’s decisions can alter the probability of detection. The problem can be formulated as a bilevel program in which the attacker, having a limited budget, chooses critical arcs to install detectors and enhances the interdiction probability of those arcs. The bottom level problem is a two-stage problem to maximize the flow in the network by smugglers. A bilevel decomposition algorithm has been applied to solve the problem by adding some Benders’ cuts iteratively. We applied a successive method, to deal with non-linearity arising in the probability measure of each path. A case study of drug trafficking network is applied to recognize which countries have the most significant effect in interdicting the drug trafficking network. The police can concentrate on those areas to decrease drug flow. Our results demonstrate that if the critical arcs are chosen wisely to enhance and the probability of opium seizers decrease slightly, a significant reduction in the expected total flow of drugs can be achieved.

Scarce resources may cause delay in completion of a project on time. In this research, a multi-objective decision making model is developed for scheduling multi-mode resource constraint scheduling problem in the presence of uncertain resources. The objectives are profit, execution cost and completion time. To develop this idea, a multi-objective non-linear mixed integer programming model is developed where resource availability is not deterministic and expressed by triangular probability function. In continue a multi-objective weighting genetic algorithm is proposed (MOWGA) which is flexible enough to be used in real projects. To verify the performance of the proposed method, a number of experiments are solved and results are analyzed. The outcomes, indicated that while resource uncertainty increases, higher complexity in schedules is observed. It is also found that optimizing one objective function is not necessarily resulted in optimizing the others. The MOWGA is then successfully applied for a project with real data.

The industrial sector has historically been linked to the prosperity, development and evolution of nations, hence to the genesis of the philosophy of competitiveness, mainly at the manufacturing level. An environment is in perpetual adaptation to trends, and the best example is the change of industrial ideology, as was the case in the past. The global society is facing the same challenges. Customer demands are becoming more and more specific and personalized, which means that factories have to innovate in terms of production and management of mudas in an eco-environmental context closely followed by several global organizations. Information and communication technologies have become the joker to master in order to stay in a market that is global and very competitive. At the heart of this evolution is the emergence of the Industry 4.0 concept, which includes a key element that is intelligent production in factories of the future that can meet different obstacles. The purpose of the current research on one hand is to highlight the relation between I4.0, smart manufacturing and smart factory, and on the other hand to present a synthesis of Industry 4.0 national initiatives linked to the fourth industrial revolution worldwide.

This paper examines the impacts of three factors include the service, price, and discount on the supply chain’s profit. We consider a supply chain, including one traditional retailer and two manufacturers. By using the game-theoretic approach, we derive optimal solutions and analyze competition between members under two scenarios: (1) the retailer buys the products from two manufacturers without price discount contracts, i.e. no products are sold with price discount contract. (2) The retailer buys the product from one of the manufacturers with price discount contracts. We find that the price discount rate and the service level are very effective on the demand and profit of supply chain members and determining the appropriate discount rate is very important. The results show that increasing the service provided by the retailer does not necessarily increase the profit of the manufacturer and he should set an appropriate discount rate to increase his profit. Our work contributes to three aspects: (1) joint and simultaneous examination of competition in the supply chain under the three factors of price discount, price, and service level; (2) examination of competition in the supply chain where the retailer and a manufacturer provide free service to consumers; and (3) analysis and comparison of the numerical example results in the two above scenarios according to the sensitivity analysis of various parameters.

In this paper production inventory (EPQ) model by means of incorporate cost diminution release strategy is considered. Production and demand both are simultaneous process in the real world Production and demand rate are considered to be time- linked. Two models (i) production inventory and (ii) manufacture inventory model in the midst of amalgamating cost decline delivery procedure are discussed. Mathematical formulations are provided to find optimal solution for both models. The objective of this study is to obtain optimal order measure to examine the outcome of lessening for cost release plan in the EPQ model. Best possible fabrication lot size model is developed that diminishes total cost. The sensitivity analysis is discussed for variation of different parameters.

Cargo transportation is part of the logistic sectors. Both service quality and customer satisfaction are very important for companies which provide cargo transportation services. This study aims to evaluate cargo companies via DMs (customers) preferences in Erzurum. Evaluating cargo companies is the multi-criteria decision making (MCDM) problem and DMs often use uncertain linguistic terms to express their assessments because DMs hesitate among different linguistic terms to provide their preferences. In this study, an integrated MC-HFLTS&MAIRCA (Multi-criteria Hesitant Fuzzy Linguistic Term Set and Multi Attribute Ideal-Real Comparative Analysis) method is used for evaluating and selecting the best cargo company. From this point of view, alternatives, criteria and DMs are defined and the integrated method is applied for the selection of the best cargo company. In order to test the results, MABAC, TOPSIS and VIKOR methods were used.