International Journal of Industrial Engineering & Production Research

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  The traveling salesman problem is a well-known and important combinatorial optimization problem. The goal of this problem is to find the shortest Hamiltonian path that visits each city in a given list exactly once and then returns to the starting city. In this paper, for the first time, the shortest Hamiltonian path is achieved for 1071 Iranian cities. For solving this large-scale problem, two hybrid efficient and effective metaheuristic algorithms are developed. The simulated annealing and ant colony optimization algorithms are combined with the local search methods. To evaluate the proposed algorithms, the standard problems with different sizes are used. The algorithms parameters are tuned by design of experiments approach and the most appropriate values for the parameters are adjusted. The performance of the proposed algorithms is analyzed by quality of solution and CPU time measures. The results show high efficiency and effectiveness of the proposed algorithms .

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this article proposes a new algorithm for finding a good approximate set of non-dominated solutions for solving generalized traveling salesman problem. Random gravitational emulation search algorithm (RGES (is presented for solving traveling salesman problem. The algorithm based on random search concepts, and uses two parameters, speed and force of gravity in physics. The proposed algorithm is compared with genetic algorithm and experimental results show that the proposed algorithm has better performance and less runtime to be answered.

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Nowadays, competitive market creates the necessity of quality improvement in different levels of supply chains (SCs). This paper contributes to the SC coordination literature and proposes a bilateral coordination contract for optimizing pricing decisions along with quality improvement decisions in different echelons of a real case of a cell phone SC. The SC comprises a manufacturer who deals with determining the product quality, and a retailer who seeks for the optimal strategy on price, after-sale service and service level in a periodic review inventory system. The proposed bilateral wholesale price (BWP) contract is shown to be capable of simultaneous coordination of these decisions. The sensitivity analysis showed that in a market which is sensitive to quality and after-sale service as well as the product price, the proposed model facilitates investing more in such quality improvements while the members’ profitability with respect to the case without contracts is guaranteed. Moreover, it can increase the SC service level since it enables the members to hold more safety stock even under high inventory costs. Overall, the proposed coordination model on pricing, product quality, after-sale service and service level, leads to the optimal performance of the SC and its members while it is beneficial for the customers.

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In this research, we analyze a supply chain involving two competing manufacturers that sells their product through two common competing retailers. The manufacturers’ products are the same but with different brand in market. The retailers face stochastic demand where demand is a decreasing function of price with additive uncertain part. Manufacturers compete on supplying orders where retailers compete on selling price. Each manufacturer set wholesale price contract with retailers similarly. We examine supply chain coordination with wholesale price contract under competition and demand uncertainty. The analytical results show that under coordination condition, manufacturers do not obtain any positive profit and consequently the retailers intend to increase wholesale prices. On the other hand, manufacturers can increase wholesale prices until the retailers’ profit becomes zero. Hence, with a numerical study for actual cases, it is found that changing demand sensitivity and competition intensity affect the optimal decisions of ordering and pricing. Moreover, increasing in competition sensitivity, increase the supply chains’ efficiency, stocking level and selling price. The concluding remarks show that further investigation is required for possibility of coordination under competition by other contractual mechanisms.

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This paper develops an approximate cost function for a three-echelon supply chain that has two suppliers, a central warehouse and an arbitrary number of retailers. It takes an integrated approach to multi-echelon inventory control and order-splitting problems. It assumes that all facilities apply continuous review policy for replenishment, demand at the retailers follows a Poisson process, and lead times are stochastic with no predetermined probability distribution. Unsatisfied demand is considered as lost sales at the retailers and backlogged at the warehouse and suppliers. Due to information sharing between the existing echelons, order quantity at each higher level is assumed to be an integer multiple of the lower level. Order placed by the warehouse gets divided between the two suppliers and re-order point is not restricted at the warehouse or suppliers. The main contribution of this paper is its integrated approach and the practical assumption that it uses for the order arrival sequence and the unsatisfied demands. It adds two suppliers as the third echelon to the traditional two-echelon supply chain and considers dynamic sequence of orders arrival to the warehouse at each cycle. The fact that inventory control and sourcing decisions are interdependent and act as the main challenge of supply chain management, considering them in an integrated model can significantly influence operating costs and supply chain’s efficiency. Such approach can even have greater impact when blended with practical assumptions that consider lead-time as unpredictable and unsatisfied demand as lost sales. Total cost of the three-echelon inventory system is approximated based on the average unit cost and its accuracy is assessed through simulation. Numerical results with relatively low errors confirms the accuracy of the model. It also shows how to further enhance its accuracy by either increasing the holding cost at all echelons or the penalty cost at the retailers.

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