International Journal of Industrial Engineering: Theory, Applications and Practice
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EFFECTIVE CLUSTER-FIRST ROUTE-SECOND APPROACHES USING METAHEURISTIC ALGORITHMS FOR THE CAPACITATED VEHICLE ROUTING PROBLEM
No full textIn this paper, three cluster-first route-second approaches are proposed to solve the capacitated vehicle routing problem (CVRP) that extends a traveling salesman problem (TSP). In the first phase, a giant tour covering all customers is built using three different metaheuristic algorithms as an ACO, a GA, and an ABCA. Then, the giant tour is split with respecting the vehicle capacity, and vehicles are loaded. In the second phase, we transform our problem into a small TSP after completing the clustering process, and a routing problem is solved based on a Branch-and-Bound algorithm. We evaluate the performance of these approaches on the benchmark problems. The computational results show that these approaches achieve high-quality results and gain an advantage in terms of CPU time. Besides, these approaches are also applied to a real-life case study related to a distribution CVRP meeting the weekly demands of a supermarket chain and provide a better routing solution
A BI-OBJECTIVE MEDICAL RELIEF SHELTER LOCATION PROBLEM CONSIDERING COVERAGE RATIOS
No full textUnder disaster circumstances, people in the impacted areas need different levels of medical services provided by the temporary or existing medical relief shelters whose medical service capability should be equal to or greater than their needs. It is an important but challenging problem to provide effective and efficient medical or relief services to the affected people. This study proposed a bi-objective mathematical programming model to overcome this challenging situation considering the patients' severities, medical service level, and geographical locations under disaster circumstances. The proposed bi-objective mathematical model intends to determine the appropriate locations for temporary medical relief shelters (MRS), specifying the service level of MRS and plan the logistics network for medical supplies. The objective is to achieve the maximum coverage of medical relief service and the minimum logistics costs, including the construction and operating costs of temporary MRSs and the procurement and transportation costs of medical supplies from medical deployment centers simultaneously. This paper solves a bi-objective medical shelter location problem with differential coverage ratios, using the non-dominated sorting genetic algorithm II (NSGA-II) and the modified NSGA-II (mNSGA-II) to find the Pareto front. Due to the sensitivity of those algorithms to parameter values, the Taguchi method is used to tune the parameters of the algorithms. We have chosen five measures into two groups. Qualitative metrics include the number of Pareto solutions (NPS), diversity metric, and spacing metric, and quantitative metrics include mean ideal distance (MID) and calculation times to evaluate the performance of our proposed algorithms. Various test problems of different sizes are tested to compare the performance of the NSGA-II and mNSGA-II. The computational results compared the pros and cons of two algorithms in solving the bi-objective medical relief shelter location problem
GUIDELINES RELATED TO PERFORMANCE RESTRICTIONS IN THE PRODUCT-SERVICE SYSTEM: A SYSTEM DYNAMICS APPROACH
No full textThe dynamic behavior of a Product-Service System is influenced by the delays regarding customer decisions and nonlinearities of perceptions. These factors can generate performance restrictions when services are added to products without managerial review, since System Dynamics models that address the Product-Service System do not provide a detailed description of the operational dynamics of services or the relationship of the system with customer perception. Thus, in this article a model is proposed to represent graphically the dynamic behavior of the service aggregation to deliver value. Using the System Dynamics methodology, the results included a conceptual model showing the main dynamic factors, a structural model and its mathematical description. This enables the contribution: the establishment of guidelines for management and product development process. Four guidelines are detailed highlighting the importance of considering the satisfied condition, the ease of the obtainment and consumption of value and the operational and control issues
AN EFFICIENT SIMULATED ANNEALING FOR A HYBRID FLOW SHOP SCHEDULING PROBLEM WITH SEQUENCE-DEPENDENT SETUP TIMES AND TWO OBJECTIVES
No full textThe paper studies the problem of production scheduling of a set of independent jobs in the g-stage hybrid flow shop. To maximize external and internal efficiency, performance optimization of two functions, including maximum completion time and total tardiness, is intended simultaneously. Due to the dependency of scheduling activities on the times required to prepare the production processes, setup times are considered in the scheduling configurations. The bi-objective simulated annealing is proposed to handle the problem that belongs to the NP-hard class. The proposed algorithm is compared with another efficient algorithm in the literature (namely MOSA). The performance criterion based on the concept of data envelopment analysis, the Free Disposal Hull approach (FDH), is used to estimate the algorithm's efficiency with respect to a set of efficient solutions. The results confirm that the set of efficient solutions of the proposed algorithm is more efficient than another algorithm
INVESTMENT SELECTION AND EVALUATION FOR CHINA EXPRESS DELIVERY MARKET
Get PDFChina’s express industry has experienced phenomenal growth in recent years. More investors are considering entering the express delivery industry in China. Investors are particularly interested in understanding the following questions: 1) How do existing express delivery companies in China manage their businesses? 2) What are the strengths and weaknesses of these companies if there is potential collaboration? This study investigates the top 12 express delivery companies in China and independently evaluates their business performance. To this end, we first employ the uncertain linguistic variables (ULV) to simulate the uncertainties of a decision-making process. Then, we propose a novel weighted method integrating subjective and objective evaluations into a unique value and rank the 12 express delivery companies. Compared with conventional methods, the proposed model mitigates the adverse effects of uncertainty while providing a practicable approach to incorporate the sentiments of area experts. This model can be easily applied to other industries and markets
DEFINING AND MODELING RISKS IN SERVICE SUPPLY CHAINS
No full textRisk management in supply chains is of growing importance and has been studied extensively in manufacturing supply chains. However, risk in service supply chains (SSCs) is largely neglected. Since SSCs are not immune to disruptions, there is a need to study and understand supply chain risks from a service perspective. This paper sets out to identify, define and examine risks in SSCs. Using a systematic literature review, the paper explicitly defines seven risk types associated with SSCs: financial, relationship, demand, operational, service delivery, Information technology (IT), and external risks. To gain a deeper understanding of these risks and their consequences, a structural model of the relationships among them was developed using ISM and MICMAC. This study helps us to identify and understand all the risks that need to be assessed in SSCs, which in turn would lead to enhanced risk management and business sustainability
INFLUENCE OF MAN-MACHINE RATIO ON SYSTEM PERFORMANCE OF ONE-PERSON-MULTI-MACHINE SERIES PRODUCTION LINE
Get PDFThe one-person-multi-machine assignment is a typical feature of lean production systems. The major disadvantage of this type of assignment is that it could cause system delay due to human failure. Therefore, it is important to analyze the degree of efficiency loss among machines caused by interference between operators and machines. In this paper, a methodology is developed based on the decomposition technique. The whole U-shape production line is modeled as several subsystems where the efficiency loss mentioned above can be treated as machine failure. Hence, each subsystem can be simplified as an unreliable workstation with a certain failure rate. With finite buffers between consecutive subsystems, the influence of human failure can be analyzed and verified with an industry-based case study. Data was collected from an automotive electronics plant as well as corresponding computational and simulation test results. Statistics show that the method developed in this paper will make contributions to solving industrial problems
A MIXED INTEGER NONLINEAR MODEL FOR AIR REFUELING OPTIMIZATION TO SAVE FUEL IN MILITARY DEPLOYMENT OPERATIONS
No full textFuel is a critical strategic asset for military aviation operations. Air refueling offers both the opportunity to extend aircraft range, and the potential to save fuel by enabling a transport aircraft to depart with less fuel in exchange for additional cargo. We evaluate the practicality of air refueling in terms of fuel savings versus distance and cargo quantity by introducing two non-linear optimization models that examine the tradeoff between departure fuel weight and loaded cargo for given origin, destination, tanker base positions, and freight loads. Our models capture realistic operational procedures of air refueling, and include complex fuel consumption calculations for multiple cargo and tanker aircraft. We optimize initial fuel and cargo amounts, and rendezvous points for air refueling, for multiple cargo and tanker aircraft in a deployment scenario. We use two numerical example scenarios to demonstrate that substantial fuel savings are possible
EQUIPMENT RESOURCE OPTIMIZATION BASED ON EFFICIENCY EVALUATION AND COMPARATIVE ADVANTAGE
No full textIn this study, a method for optimizing equipment resources based on efficiency evaluation and the relative advantage relationship is proposed. An efficiency evaluation and optimization model are also constructed, and the corresponding algorithm is designed. The effects of altering the decision-matrix canonical method and quantity discount on multi-attribute decision-making are studied by investigating the available feasible solutions. The results show that the proposed efficiency evaluation and optimization model can yield several groups of optimal feasible solutions. Additionally, combining it with a multi-attribute decision model can enable it to effectively select and rank feasible solutions while avoiding the adverse effect of different decision-specification methods on the decision-making result. The decision method and quantity discount considerably influence the multi-attribute decision-making results, implying their importance when optimizing the equipment resources with respect to a manufacturing process
PRODUCTION DECISION RESCHEDULING OF PREFABRICATED BUILDING PARTS SUBJECT TO INTERFERENCE FROM THE ARRIVAL OF NEW ORDERS
No full textDisruption events that occur during the production of prefabricated components present challenges for the feasibility of an original production plan. Therefore, rescheduling is of great significance in production management. In this paper, we study a rescheduling decision method for prefabricated building component production where the insertion of new orders is considered a disruption. We develop a rescheduling model for precast production to minimize the maximum completion time and design an improved grey wolf intelligent algorithm to solve the model. Furthermore, we take the initial plan as the base and establish a profit-loss function based on the saved time or the delay generated by the rescheduling plan. Finally, we conduct a case study that verifies the validity and feasibility of the rescheduling decision method and model. Our results contribute to the existing literature on rescheduling decisions by improving the stability of a production system