International Journal of Industrial Engineering: Theory, Applications and Practice
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SIMULATION MODEL OF A VERTICALLY INTEGRATED SUPPLY CHAIN: A CASE STUDY
No full textThis paper reports on the successful development and use of simulation for the analysis of a vertically integrated supply chain. Simulation has only recently been applied to the analysis of industrial supply chains and this model differs from existing work in this area in that the manufacturing function is modelled in detail. This is contrast to the logistical models developed using simple lead times to represent manufacturing. This paper reports on the scale of system being analysed, the type of data required to populate such a model, such as product routings, standard times, work centre capacities and shift cycles and the level of detail included in the stl!dy and the performance outputs from the model. Using this model experiments were carried out to analyse the effect of stocking policies, production controls, changing demand trends and the effect of forecasting and information sharing on supply chain performance measures. One such experiment to determine the effective trade-off from operating three different finish stocking policies is outlined in detail. These experiments provide management with a useful tool for decision support in relation to both strategic and production strategies
APPLYING MIXED INTEGER PROGRAMMING TO THE DESIGN OF A DISTRIBUTION LOGISTIC NETWORK
No full textFacility location (FL) and production/distribution planning are two of the most significant operational and competitive decisions for modern companies who operate worldwide. The objective of this study was the development and application of a set of mathematical programming models for both the design and management of a multi-stage distribution system to meet the continuous and tremendous pressure on companies to be flexible, competitive, and reduce production and logistic costs. The generic location allocation problem (LAP) belongs to the class ofNP-hard complexity problems. It is based on the placement of one or more facilities (the location problem) in optimum locations and on th.e concurrent assignment of customers to them (the allocation problem) in the best possible way. This requires the maximization of facility utilization, minimization of global costs, maximization of profit and service levels, and finally, it must respect a large set of physical and management constraints operating in the supply chain
OPTIMAL QUANTITY ALLOCATION DECISION IN REVENUE SHARING CONTRACT
No full textThis paper is focused on facilitating the manufacturer in making quantity allocation decisions. A revenue-sharing model with prior commitment from the retailers, two-way penalties, and reallocation of pre-allocated quantities is proposed to coordinate a supply chain comprising one manufacturer and two retailers facing stochastic demand. Over and under-purchase penalties are introduced to motivate the retailers to commit close to expected demand. In contrast, the under-supply penalty is presented for the manufacturer to compensate the stock-out loss of the retailers. Reallocation of pre-allocated quantities is also allowed to reduce the allocation risk of the manufacturer. The analysis reveals that the proposed model helps motivate stakeholders to share accurate demand information through a reward-penalty mechanism. Moreover, coordination improves the performance of the supply chain with a “win-win” solution for the stakeholders. The case study results reveal that the proposed model through the reward-penalty mechanism ensures true information sharing. Furthermore, reallocation reduces the possibility of waste. This is the first revenue-sharing model, including prior commitments, two-way penalties, and reallocation of pre-allocated quantities
THE ROLE OF CREW ROSTERING IN SUSTAINABLE OPERATIONS: A CASE STUDY IN AIRLINES
No full textThe airline industry has evolved significantly in recent years, and the emphasis on minimizing the cost and risk of operational disruptions has been shifted, in part, to satisfaction and fairness in the assignment of crew members. The crew rostering is the phase of flight schedules in which crew members are assigned to rosters based on their preferences and fairness in terms of balanced flight times between crew members. The satisfaction of the crew members depends on how much their preferences are met in the rosters. In this study, the crew rostering problem with cabin members' preferences is formulated as a mixed-integer goal programming model with three objective functions: total satisfaction score, deviation from average satisfaction score, and deviation from average flight hours. The importance of these objectives is imprecise from the flight management system perspective, so this study proposes a fuzzy goal programming model to solve the crew rostering problem with the preferences. The paper is organized based on a case study gathered from an airline in Kuwait. The results showed that incorporating pilot preferences leads to better rosters in terms of pilot satisfaction. However, increasing the number of pilots in consideration or the flight evaluation percentage does not lead to better rosters. The case study also sheds light on the links between the crew roster and sustainable operations.
MULTI-OBJECTIVE COLLABORATIVE HARVEST WORKFORCE PLANNING FOR RICE SEED PRODUCTION CONSIDERING WORKLOAD BALANCE AND WORKER SATISFACTION
Get PDFThis paper proposes a collaborative harvest workforce (CHW) model that generates a worker-sharing schedule for farm owners tasked to produce rice seeds. The CHW model is a multi-objective optimization model with four objectives. The first two objectives are to minimize the average total cost and the number of harvesting days. The third objective is to minimize the difference in workloads, and the fourth is to maximize the workers' total satisfaction. Farmlands were categorized into three difficulty levels with different satisfaction scores. The weighted sum and the weighted Tchebycheff methods were used to solve the CHW model, and the weights of the four objectives were computed based on expert opinions. All parties could benefit from this collaborative harvesting planning model and achieve sustainable relationships; farm owners could share costs and save harvesting time, while the workers could be more satisfied and reduce their risk of injury
A BRANCH-AND-BOUND ALGORITHM FOR TWO-COMPETING-AGENT SINGLE-MACHINE SCHEDULING PROBLEM WITH JOBS UNDER SIMULTANEOUS EFFECTS OF LEARNING AND DETERIORATION TO MINIMIZE TOTAL WEIGHTED COMPLETION TIME WITH NO-TARDY JOBS
No full textRecent scheduling studies focus on variable job-processing times and multi-agent problems simultaneously, but none of them studied with jobs under the simultaneous effect of learning and deterioration. This paper studies a two-competing-agent single-machine scheduling problem with jobs under simultaneous learning and deterioration effect. The goal is to find an optimal solution to minimize the total weighted completion time for the first agent, subject to the restriction that no tardy job is allowed for the second agent. According to our current literature knowledge, this paper will be the first one with these specifications. For this problem, a two-stage methodology is developed in the study. In the first stage, heuristics are proposed to find the near-optimal solution of which is used as input for the second stage. For the second stage, a branch-and-bound algorithm along with several dominances and a lower bound is developed to find the optimal solution. Computational experiments are provided to further measure the performance of the proposed algorithms
STATISTICAL ANALYSIS AND CASE INVESTIGATION OF FATAL FALL-FROM-HEIGHT ACCIDENTS IN THE CHINESE CONSTRUCTION INDUSTRY
No full textA fall-from-height accident is considered a major leading cause of construction fatalities. The analysis of accident characteristics could offer effective guidance to the construction industry to prevent falls from heights. By using accident statistical analysis and typical case investigation, this study indicates the basic pattern and reviews in detail the conditions of a fall-from-height incident in China. The result shows that more fatal fall-from-height accidents occur from 10 a.m. to 11 a.m. and 3 p.m. to 4 p.m. Accidents on weekdays are nearly as many as on weekends. The lowest incidence month is February. Accidents resulting in one death take most of the total. Furthermore, not fastening a safety belt is among the leading reasons workers die after falling from heights. Victims in fall-from-height accidents are mostly male workers. Fall heights are most often less than 15 meters. This study serves to alert construction safety policymakers to diagnose the current state of fall-from-height accidents and provides a targeted direction for improving the safety record of work at height
ANALYSIS OF SPECIFIC STATES IN NONPARAMETRIC DECISION-MAKING METHODS
No full textDecision-making techniques have now been developed more than ever before; however, it does not mean that the proposed models are impeccable and flawless. One of the most common multi-criteria decision-making methods is Data Envelopment Analysis (DEA), which is a nonparametric decision-making method as the weights of evaluation attributes are unknown in this model, and it is necessary to employ Linear Programming (LP) models to find them. This paper aims to analyze some specific states in existing problems in this area for the solution of which basic models might be slightly inefficient. Therefore, a few mathematical theorems are introduced and proven in this study to solve these problems. The proposed method avoids increasing the number of decision-making attributes and constraints in non-input DEA models. The results show that the proposed approach improved the simplex algorithm's performance in solving the related linear programming models
A SIMULATION STUDY OF PREDICTIVE CONDITION-BASED MAINTENANCE STRATEGY FOR ITEMS PURCHASED WITH EXTENDED WARRANTY
No full textThis paper studies predictive condition-based maintenance (CBM) and failure-based replacement for a degrading machine protected by an extended warranty policy. After the warranty expires, replacement is made based on the number of major failures, and preventive actions are scheduled based on condition monitoring. The aim is to develop a simulation model for system life cycle cost (LCC) analysis with respect to decision variables, including the length of the warranty period, the maximum number of failures allowed after the warranty period, and the degradation threshold for triggering PM action in CBM. Moreover, the CBM system may be affected by two types of error: prognosis error and maintenance human error. The proposed model incorporates human and prognosis errors into the global system optimization model. Optimal warranty and replacement policies, along with optimal CBM implementation policy, are derived to ensure minimum long-run LCC. This study also discusses the effects of the error parameters on customers’ decisions and costs
CENTRALIZED VS. DECENTRALIZED PLANNING OF DYNAMIC FLOWS ON CAPACITATED TRANSPORT NETWORKS: A COMPARATIVE COMPUTATIONAL STUDY
No full textThis paper studies the problem of planning dynamic flows on capacitated transport networks. The main contribution of this study is to compare planning approaches that adopt similar routing and scheduling strategies with different levels of decentralization and investigate the impact of this difference on their computational efficiency. We compare the computational performance of two recent hybrid approaches, one centralized and the other decentralized, for routing and scheduling multi-commodity flows on capacitated transport networks using five performance and computational measures for twelve case problems. The numerical results of the performance and computational metrics for each case problem are recorded and analyzed. The main findings of this study are that solving each network flow case problem in the desterilized environment provides the same minimum flow times for all objects from their source nodes to predetermined terminal nodes with a significant decrease in the model size parameters and memory usage required by the solver, and increase in the number of sub-problems solved by the solver. All case problems reveal the same computational trade-offs, and that raises the credibility of the study findings