Efficient priority rules for dynamic sequencing with sequence-dependent setups
, Pages: 367-384
A. S. Xanthopoulos, D. E. Koulouriotis, A. Gasteratos and S. Ioannidis PDF (685K)
Abstract: This article addresses the problem of dynamic sequencing on n identical parallel machines with stochastic arrivals, processing times, due dates and sequence-dependent setups. The system operates under a completely reactive scheduling policy and the sequence of jobs is determined with the use of dispatching rules. Seventeen existing dispatching rules are considered including standard and setup-oriented rules. The performance of the system is evaluated by four metrics. An experimental study of the system is conducted where the effect of categorical and continuous system parameters on the objective functions is examined. In light of the results from the simulation experiments, a parameterized priority rule is introduced and tested. The simulation output is analyzed using rigorous statistical methods and the proposed rule is found to produce significantly better results regarding the metrics of mean cycle time and mean tardiness in single machine cases. In respect to three machine cases, the proposed rule matches the performance of the best rule from the set of existing rules which were studied in this research for three metrics.
Keywords: Dynamic sequencing, Discrete event simulation, Sequence-dependent setups, Dispatching rules
A hybrid metaheuristic method to optimize the order of the sequences in continuous-casting
, Pages: 385-398
Achraf Touil, Abdelwahed Echchtabi, Adil Bellabdaoui and Abdelkabir Charkaoui PDF (685K)
Abstract: In this paper, we propose a hybrid metaheuristic algorithm to maximize the production and to minimize the processing time in the steel-making and continuous casting (SCC) by optimizing the order of the sequences where a sequence is a group of jobs with the same chemical characteristics. Based on the work Bellabdaoui and Teghem (2006) [Bellabdaoui, A., & Teghem, J. (2006). A mixed-integer linear programming model for the continuous casting planning. International Journal of Production Economics, 104(2), 260-270.], a mixed integer linear programming for scheduling steelmaking continuous casting production is presented to minimize the makespan. The order of the sequences in continuous casting is assumed to be fixed. The main contribution is to analyze an additional way to determine the optimal order of sequences. A hybrid method based on simulated annealing and genetic algorithm restricted by a tabu list (SA-GA-TL) is addressed to obtain the optimal order. After parameter tuning of the proposed algorithm, it is tested on different instances using a.NET application and the commercial software solver Cplex v12.5. These results are compared with those obtained by SA-TL (simulated annealing restricted by tabu list).
Keywords: Steel-making, Continous-casting, Hybrid metaheuristics, Simulated annealing, Genetic algorithm, Tabu list
A study on the ranking performance of some MCDM methods for industrial robot selection problems
, Pages: 399-422
Prasad Karande, Edmundas Kazimieras Zavadskas and Shankar Chakraborty PDF (685K)
Abstract: In this paper, the ranking performance of six most popular and easily comprehensive multi-criteria decision-making (MCDM) methods, i.e. weighted sum method (WSM), weighted product method (WPM), weighted aggregated sum product assessment (WASPAS) method, multi-objective optimization on the basis of ratio analysis and reference point approach (MOORA) method, and multiplicative form of MOORA method (MULTIMOORA) is investigated using two real time industrial robot selection problems. Both single dimensional and high dimensional weight sensitivity analyses are performed to study the effects of weight variations of the most important as well as the most critical criterion on the ranking stability of all the six considered MCDM methods. The identified local weight stability interval indicates the range of weights within which the rank of the best alternative remains unaltered, whereas, the global weight stability interval determines the range of weights within which the overall rank order of all the alternatives remains unaffected. It is observed that for both the problems, multiplicative form of MOORA is the most robust method being least affected by the changing weights of the most important and the most critical criteria.
Keywords: MCDM, WSM, WPM, WASPAS, MOORA, Reference point approach, MULTIMOORA, Industrial robot selection, Rank, Sensitivity analysis
Impact of future price increase on ordering policies for deteriorating items under quadratic demand
, Pages: 423-436
Nita H. Shah, Mrudul Y. Jani and Urmila Chaudhari PDF (685K)
Abstract: When a supplier announces a price increase at a certain time in the future, for each retailer it is important to choose whether to purchase supplementary stock to take benefit of the current lower price or procure at a new price. This article focuses on the possible effects of price increase on a retailer’s replenishment strategy for constant deterioration of items. Here, quadratic demand is debated; which is appropriate for the products for which demand increases initially and subsequently it starts to decrease with the new version of the substitute. We discuss two scenarios in this study: (I) when the special order time coincides with the retailer’s replenishment time and (II) when the special order time falls during the retailer’s sales period. We determine an optimal ordering policy for each case by maximizing total cost savings between special and regular orders during the depletion time of the special order quantity. Scenarios are established and illustrated with numerical examples. Through, sensitivity analysis important inventory parameters are classified. Graphical results, in two and three dimensions, are exhibited with supervisory decision.
Keywords: Inventory, Deteriorating items, Price increase, Quadratic demand
Equilibrium solution of non-cooperative multiobjective bimatrix game of Z-numbers
, Pages: 437-450
Mahdieh Akhbari and Soheil Sadi-Nezhad PDF (685K)
Abstract: In this paper we introduce the concept of equilibrium for a non-cooperative multiobjective bimatrix game with payoff matrices and goals of Z-Numbers. In the recent studies of the authors, the problem of finding equilibrium for a non-cooperative bimatrix of Z-Numbers are investigated. Multiple payoffs are often dealt with in games because a decision making problem under conflict usually involves multiple objectives or attributes such as cost, time and productivity. We let each of the objectives of the problem correspond to each of the payoffs of the game. To aggregate multiple goals, we employ two basic methods, one by weighting coefficients and the other by a minimum component. In order to find the equilibrium solution in such circumstances, we developed a mathematical programming problem to maximize the aggregated goal subject to constraint of satisfying an aspiration level of confidence in the equilibrium solution. Finally a method is presented to determine the equilibrium solution with respect to the level of achievement to the aggregated goal.
Keywords: Non-cooperative game theory, Z-number, Z-number type payoffs, Z-number type goals, Equilibrium solution
Designing an advanced available-to-promise mechanism compatible with the make-to-forecast production systems through integrating inventory allocation and job shop scheduling with due dates and weighted earliness/tardiness cost
, Pages: 451-462
Masoud Rabbani, Mina Monshi, Neda Manavizadeh Moeen Sammak Jalali PDF (685K)
Abstract: In the competitive business world, applying a reliable and powerful mechanism to support decision makers in manufacturing companies and helping them save time by considering varieties of effective factors is an inevitable issue. Advanced Available-to-Promise is a perfect tool to design and perform such a mechanism. In this study, this mechanism which is compatible with the Make-to-Forecast production systems is presented. The ability to distinguish between batch mode and real-time mode advanced available-to-promise is one of the unique superiorities of the proposed model. We also try to strengthen this mechanism by integrating the inventory allocation and job shop scheduling by considering due dates and weighted earliness/tardiness cost that leads to more precise decisions. A mixed integer programming (MIP) model and a heuristic algorithm according to its disability to solve large size problems are presented. The designed experiments and the obtained results have proved the efficiency of the proposed heuristic method.
Keywords: Advanced Available-to-Promise (AATP), Make-to-Forecast (MTF), Batch /real-time mode ATP, Jobshop scheduling, Weighted earliness/tardiness cost, Inventory allocation
Integrated supply chain inventory model with quality improvement involving controllable lead time and backorder price discount
, Pages: 463-480
Prashant Jindal and Anjana Solanki PDF (685K)
Abstract: For the past four decades the integrated vendor and buyer supply chain inventory model has been an interesting topic, but quality improvement of defective items in the integrated inventory model with backorder price discount involving controllable lead time has been rarely discussed. The aim of this paper is to minimize the total related cost in the continuous review model by considering the order quantity, reorder point, lead time, process quality, backorder price discount and number of shipment as decision variables. Moreover, we assume that an investment function is used to improve the process quality. The lead time demand follows a normal distribution. In addition, the buyer offers backorder price discount to motivate the customers for possible backorders. There are some defective items in the arrival lot, so its treatment is also taken in account in this paper. We develop an iterative procedure for finding the optimal values of decision variables and numerical example is presented to illustrate the solution procedure. Additionally, sensitivity analysis with respect to major parameters is also carried out.
Keywords: Lead time, Crashing cost, Integrated supply chain inventory model, Backorder price discount, Quality improvement
A multi-objective location routing problem using imperialist competitive algorithm
, Pages: 481-488
Amir Mohammad Golmohammadi, Shahrokh Amanpour Bonab and Amir Parishani PDF (685K)
Abstract: Nowadays, most manufacturing units try to locate their requirements and the depot vehicle routing in order to transport the goods at optimum cost. Needless to mention that the locations of the required warehouses influence on the performance of vehicle routing. In this paper, a mathematical programming model to optimize the storage location and vehicle routing are presented. The first objective function of the model minimizes the total cost associated with the transportation and storage, and the second objective function minimizes the difference distance traveled by vehicles. The study uses Imperialist Competitive Algorithm (ICA) to solve the resulted problems in different sizes. The preliminary results have indicated that the proposed study has performed better than NSGA-II and PAES methods in terms of Quality metric and Spacing metric.
Keywords: Optimization, Mathematical Programming, Locating storage unit, Vehicle routing, The meta-heuristic Algorithm
Replenishment policy for non-instantaneous deteriorating items in a two storage facilities under inflationary conditions
, Pages: 489-506
Chandra K. Jaggi, Sunil Tiwari and Satish K. Goel PDF (685K)
Abstract: The present study investigates an inventory model for non-instantaneous deteriorating items under inflationary conditions with partially backlogged shortages. In today’s market structure consumers are looking for goods for which there is a delay in deterioration. At the same time, the consumers’ willingness to wait has been decreased over time, which leads to lost sales. Moreover in financial decision-making, the effects of inflation and time value of money cannot be oblivious to an inventory system. In this scenario, managing inventory of goods remains a challenging task for the decision makers, who may also have to rent warehouse under different prevailing factors such as, bulk discount, limited space in the retail outlet, or increasing inflation rates. With a focus on reduction of costs and increasing customer service, warehouse decision models are crucial for an organization’s profitability. Hence a mathematical model has been developed in the view of above scenario, in order to determine the optimal policy for the decision maker, by minimizing the present worth of total cost. The optimization procedure has been illustrated by a numerical example and detailed sensitivity analysis of the optimal solution has been performed to showcase the effect of various parameters. Managerial implications has also been presented to aid the decision making process.
Keywords: Inventory, Non-instantaneous deterioration, Two-warehouse, Partial backlogging, Inflation
A non-permutation flowshop scheduling problem with lot streaming: A Mathematical model
, Pages: 507-516
Daniel Rossit Fernando Tohmé, Mariano Frutos, Jonathan Bard and Diego Broz PDF (685K)
Abstract: In this paper we investigate the use of lot streaming in non-permutation flowshop scheduling problems. The objective is to minimize the makespan subject to the standard flowshop constraints, but where it is now permitted to reorder jobs between machines. In addition, the jobs can be divided into manageable sublots, a strategy known as lot streaming. Computational experiments show that lot streaming reduces the makespan up to 43% for a wide range of instances when compared to the case in which no job splitting is applied. The benefits grow as the number of stages in the production process increases but reach a limit. Beyond a certain point, the division of jobs into additional sublots does not improve the solution.
Keywords: Non-Permutation Flowshop Scheduling, Lot Streaming, Makespan
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