International Journal of Industrial Engineering: Theory, Applications and Practice
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BIVARIATE DEPENDENCY FOR THE VEHICLE ROUTING PROBLEM WITH TIME WINDOWS
No full textThe main purpose of the vehicle routing problem (VRP) is to deliver a set of customers with known demands on minimum travel routes starting and terminating at the same depot. The vehicle routing problem with time windows (VRPTW) requires the delivery made in a specific time window for every customer and returning to the depot before a due time. Contrary to current research, an estimation of distribution algorithm-based approach is proposed and developed to solve the problem and implement the solution. The approach mentioned makes use of a probability model based on the Pearson's correlation coefficient to describe the distribution of the solution space. Different and diverse instances served as input and test parameters in order to show that the estimation of any relationship and/or interaction between vertices on the sequence of the VRPTW solution can be improved. A better position for each vertex on the sequence can be estimated through a probability model using the Pearson's correlation coefficient
Periodic Due Date Assignment with Family Setups
No full textIn this study we consider a single machine due date assignment problem involving dynamic job arrivals and family setups. The due date quotation process that we investigate is based on periodically generating schedules of new and existing jobs, and quoting due dates using a function of completion times of jobs in the schedule. We propose a mixed integer linear programming formulation to solve the underlying scheduling problem. We also present a function to quote due dates for new jobs. Wereport the performance of the proposed due date quotation process based on the simulation study that is carried out under various shop and solution procedure parameters
Industrial Service Flexibility and Regional Network Collaboration in Industrial Clusters
No full textIndustry clusters link firms in specific industries in a geographical area and comprise vertical and horizontal business supply chain partners. Industrial service flexibility (ISF) is strongly related to goal-driven innovation within clusters in a regional network. The regional network collaboration (RNC) facilitates commerce and service relationships by coordinating production and merchandise flows. This study reviews relevant academic literature and divides the dimensions of ISF efficiency into “internal ISF” and “external ISF”. This study further explores the influential factors of RNC as dimensions of “geography”, “resource” and “network”. This study finds that the “distance proximity” and “company scale” are not significant to the efficiency of internal and external ISFs. “Talent resource” and “information network” provide significant linkages to the efficiency of internal and external ISFs. Finally, in order to improve the efficiency of ISF, “network information” is important to the internal ISF, and “network interaction” is an indispensable element in external ISF
ORDER CONSOLIDATION PROBLEM ON GRAPHS WITH CUBICITY P
No full textWe consider the problem of consolidating compatible orders for a batch production process where its downstream process differentiates its output to yield final products that are characterized by p different attributes. In particular, we consider the case where the customer orders are considered to be compatible enough to be processed together in the same batch when their difference in each attribute is no more than a specific tolerence. In such case, the compatibility relationship among orders can be represented by the graph known as the graph with cubicity p. We show that the problem of optimizing the batch production in this case is NP-hard even when we have only two attributes. Then, we develop a simple optimal algorithm for the case with a single attribute. This result also shows, for the first time, that the Kr packing is solvable in polynomial time on the graph with cubicity 1 which is also knonw as the unit interval or indifference graph
SIMULATION MODELLING AND INNOVATIVE APPLICATION OF MULTI-CRITERIA DECISION MAKING RULE FOR MINIMIZING MAKESPAN IN A LARGE SCALE PRESS-SHOP
No full textSequencing and scheduling of jobs plays an essential role in improving the performance of the job shop production system. In this paper, a detailed study has been made at an auto ancillary unit to prioritize the jobs in a press-shop. The press-shop considered in this study is similar to a typical job-shop environment. The press-shop is consisting of 32 work stations and can process a maximum of 115 job variants according to the monthly demand. The jobs are processed based on their sequence of operation. The main objective of this paper is to develop a realistic simulation model of the shop floor and to evaluate its performance measures using Priority Dispatching Rules (PDR’s) rules. Static PDR’s and Multi-Criteria Decision Making (MCDM) approach are used in this study to evaluate the performance of the press-shop. Simulation model of the press-shop has been developed using Discrete Event Simulation (DES) package ‘ARENA’. The proposed simulation model is integrated with an innovative application of MCDM approach to prioritize the jobs using the ‘Technique for Order of Preference by Similarity to Ideal Solution’ (TOPSIS). Actual demand scenarios of the press-shop has been simulated using the proposed simulation model and the results are compared with the existing practice. The proposed approach is found to be effective and the monthly demand of the customers are satisfied with the reduction in the makespan. The proposed MCDM approach has been implemented in the real-time environment.
A ROBUST OPTIMIZATION MODEL FOR A LOCATION-ARC ROUTING PROBLEM WITH DEMAND UNCERTAINTY
No full textThe present article considers a location-arc routing problem (LARP) where the demands are on the edges rather than nodes on an undirected network. A mixed integer programming model is developed for an LARP with vehicle and depot capacity constraints and a fleet of heterogeneous vehicles. To adapt with reality, it is assumed that the demand of each road is an uncertain value that belongs to a bounded uncertainty set. In order to have a less conservative decision, we employ the robust optimization model proposed by Bertsimas and Sim (2003) to handle uncertainty. The proposed robust model determines a subset of potential depots to be opened along with their allocated roads in order to have an efficient location-routing decision which is immune to different realization of uncertainties. The proposed robust model is less sensitive to demand variations and is validated through Monte-Carlo simulation and relative extra cost (REC) measure with promising results. The results of sensitivity analysis showed that by increasing the degrees of conservatism, planners may employ more vehicles. Also, more depots may be opened to service all required roads
Joint ordering inventory policy for deteriorating substitute products with price and stock dependent demand
No full textThe paper deals with a single period joint ordering inventory policy of two deteriorating substitute products. Here customers' demands are linear functions of prices and instantaneous stocks of the products. When both products are available, the demand of a substitute product decreases against its own price and other's stock and increases with other's price and own stock. During stock-out of one product, a portion of demand of stock out product opts the available product because of urgent requirement. Different scenarios depending on the exhaustion of the products and nature of the demand are considered. As particular cases, models with substitutability with respect to prices and stocks separately are presented. The models are formulated to determine the optimal order quantities of each product to maximize the average total profit. The problems are solved by the generalized reduced gradient method using LINGO 12.0. The models are illustrated with numerical experiments and the impact of the model parameters on the objective function is demonstrated with the help of sensitivity analyses. Some interesting nature/ behaviour of average total profit is also outlined
AN INTEGRATED SUPPLY CHAIN WITH UNCERTAIN DEMAND AND RANDOM DEFECT RATE UNDER CARBON CAP-AND-TRADE POLICY
No full textIn this paper, we study a vendor-buyer integrated supply chain with uncertain demand and random defect rate under carbon cap-and-trade policy. We assume that the lot sent by the vendor to the buyer in each shipment contains a random fraction of defective item, and a fraction of defective items can be repaired. The defective items get screened at the buyer and sent back to the vendor, and the vendor sorts out the repairable items. At the end of each production cycle, the accumulated repairable items at the vendor are repaired in a single lot. We have taken into account the carbon emissions from all the major sources, i.e. production, inventory, transportation, repairing, and scrapping. Shortages at the buyer are partially backordered. A mathematical model is formulated to minimize the total expected cost of the supply chain by optimizing the order quantity, reorder point, and the number of shipments between the vendor and buyer under carbon cap-and-trade policy. An algorithm is proposed to solve the model. A numerical example and sensitivity analysis are presented to get some managerial insights
DESIGN OF AN OPTIMIZED FORKLIFT ROUTES FOR A FOUR-DOOR DANGEROUS GOODS MONOLAYER WAREHOUSE THROUGH GENETIC PARTICLE SWARM OPTIMIZATION ALGORITHM
No full textThe transportation and storage of dangerous goods are gradually increasing with the rapid development of China’s economy. To ensure safety and increase the operational efficiency of warehouses, we propose a four-door dangerous goods warehouse and a kind of route planning method for forklifts in the newly proposed warehouse. The main innovation of this study is to revolutionize the warehouse design through elevating the routing optimization problem of two forklifts operating in the four-door warehouse considered as a quadratic assignment problem (QAP). Theoretically, the classic particle swarm algorithm (PSO) is used to develop a unique genetic–discrete particle swarm algorithm (DPSO) to solve the proposed QAP. For the simulation, this study utilizes the database from real dangerous goods warehouse using the proposed genetic DPSO algorithm, after which it compares the results with the classic DPSO algorithm and other mathematical calculations. In conclusion, the four-door dangerous goods warehouse concept can improve the efficiency of warehouse management and reduce the cost of management under the condition of maintaining the original safety level, which provides a train of thought for the reform of the dangerous goods warehouse
COORDINATION OF A MULTI-ECHELON SUPPLY CHAIN USING SPANNING REVENUE SHARING CONTRACT
No full textUnder spanning revenue sharing contract arrangement, leading member of the supply chain negotiates for contract parameters with all other members of a multi-echelon supply chain. The downstream member simultaneously shares a specific percentage of the revenue with all other members of the supply chain. This paper investigates coordination of a three-level supply chain using spanning revenue sharing contract. The proposed contract is designed to coordinate a supply chain comprising a manufacturer, a distributor and a retailer facing stochastic demand. Wholesale price contract is used as a benchmark to evaluate the performance of the proposed contract. The conditions for coordinating the supply chain when (1) retailer is a decision maker and (2) distributor is a decision maker, are discussed under the arrangement of spanning revenue sharing contract with revenue sharing mechanism of equal additional and equal increase in percentage profit for each stakeholder. Furthermore, numerical experiments are conducted to analyze practical implementation and implications of the proposed mechanism. The research also analyzes how contract parameters affect individual profit of the retailer, the distributor, and the manufacturer under win-win solution for the participants. This research further illustrates that spanning revenue sharing contract can coordinate the supply chain with win-win solution for the participants