This paper addresses a research problem of scheduling parallel, nonidentical batch processors in the presence of dynamic job arrivals, incompatible job-families and non-identical job sizes. We were led to this problem...
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This paper addresses a research problem of scheduling parallel, nonidentical batch processors in the presence of dynamic job arrivals, incompatible job-families and non-identical job sizes. We were led to this problem through a real-world application involving the scheduling of heat-treatment operations of steel casting. The scheduling of furnaces for heat-treatment of castings is of considerable interest as a large proportion of the total production time is the processing times of these operations. In view of the computational intractability of this type of problem, a few heuristic algorithms have been designed for maximizing the utilization of heat-treatment furnaces of steel casting manufacturing. Extensive computational experiments were carried out to compare the performance of the heuristics with the estimated optimal value (using the Weibull technique) and for relative effectiveness among the heuristics. Further, the computational experiments show that the heuristic algorithms proposed in this paper are capable of obtaining near (statistically estimated) optimal utilization of heat-treatment furnaces and are also capable of solving any large size real-life problems with a relatively low computational effort.
An uncertain version of the permutation flow-shop with unlimited buffers and the makespan as a criterion is considered. The investigated parametric uncertainty is represented by given interval-valued processing times....
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An uncertain version of the permutation flow-shop with unlimited buffers and the makespan as a criterion is considered. The investigated parametric uncertainty is represented by given interval-valued processing times. The maximum regret is used for the evaluation of uncertainty. Consequently, the minmax regret discrete optimization problem is solved. Due to its high complexity, two relaxations are applied to simplify the optimization procedure. First of all, a greedy procedure is used for calculating the criterion's value, as such calculation is NP-hard problem itself. Moreover, the lower bound is used instead of solving the internal deterministic flow-shop. The constructive heuristic algorithm is applied for the relaxed optimization problem. The algorithm is compared with previously elaborated other heuristic algorithms basing on the evolutionary and the middle interval approaches. The conducted computational experiments showed the advantage of the constructive heuristic algorithm with regards to both the criterion and the time of computations. The Wilcoxon paired-rank statistical test confirmed this conclusion.
We propose to exploit the capabilities of emerging lightwave technology in order to construct photonic implementations of ''adaptive'' and ''optimized'' distributed queue dual bus (DQDB...
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We propose to exploit the capabilities of emerging lightwave technology in order to construct photonic implementations of ''adaptive'' and ''optimized'' distributed queue dual bus (DQDB) structures. These (virtual) structures are linear and multihop in nature, and they can be constructed on any physical topology by exploiting the broadcast-and-select property of WDM lightwave networks [1]-[3]. This study is important since it will allow DQDB (IEEE 802.6) networks to scale up by taking advantage of the various attractive properties of lightwave technology when they become available. The specific problem is on topological design, and it can be stated as follows: Given that the network nodes must be connected linearly and that the node positions in the network can be adjusted by properly tuning their (optical) transmitters and receivers, what is the best pattern for interconnecting them? Two sets of heuristic optimization algorithms are formulated. The first set is concerned with minimizing the maximum flow in any link. The second set of heuristics requires the knowledge of not only the traffic matrix but also the distance matrix, and these heuristics are aimed at minimizing the network-wide mean packet delay. A dynamic node migration heuristic is also formulated under which neighboring nodes swap their positions based on local information in order to preserve the optimality criterion in effect when the offered traffic changes. The performance of these heuristics are compared, some of their properties are analyzed, while their other attractive properties are highlighted via numerical examples.
In this work we present a new scheduling model for parallel machines, which extends the multiprocessor scheduling problem with release times for minimizing the total tardiness, and also extends the problem of vehicle ...
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In this work we present a new scheduling model for parallel machines, which extends the multiprocessor scheduling problem with release times for minimizing the total tardiness, and also extends the problem of vehicle routing with time windows. This new model is motivated by a resource allocation problem, which appears in the service sector. We present two class of heuristic algorithms for the solution of the problem, the first class is a class of greedy algorithms, the second class is based on the solutions of linear assignment problems. Furthermore we give a rescheduling algorithm, which improves a given feasible solution of the problem.
A heuristic algorithm, based on the criterion of having nets with larger cut numbers assigned to inner tracks and nets with smaller cut numbers assigned to outer tracks, for single row routing problem has recently bee...
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A heuristic algorithm, based on the criterion of having nets with larger cut numbers assigned to inner tracks and nets with smaller cut numbers assigned to outer tracks, for single row routing problem has recently been proposed by Tarng et al. It has been reported that this algorithm has always been able to produce the optimal solutions for all the examples tested so far. In this paper, we have proved that algorithms based on the heuristic criterion of cut numbers produce optimal solutions for instances in which all nets cover at least one common node (i.e., form a single group). However, the algorithm proposed by Tarng et al. may not produce optimal solutions for instances of multiple net groups. Thus, several possible heuristic algorithms based on the same criterion, but also taking into consideration the net grouping situation have been proposed. The experimental results show that the proposed algorithms are faster and often generate better results than the one proposed by Tarng et al. A tighter lower bound on the number of tracks required is also obtained in this paper.
The Three-Dimensional Bin Packing Problem (3BP) consists of allocating, without overlapping, a given set of three-dimensional rectangular items to the minimum number of three-dimensional identical finite bins. The pro...
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The Three-Dimensional Bin Packing Problem (3BP) consists of allocating, without overlapping, a given set of three-dimensional rectangular items to the minimum number of three-dimensional identical finite bins. The problem is NP-hard in the strong sense, and finds many industrial applications. We introduce a Tabu Search framework exploiting a new constructive heuristic for the evaluation of the neighborhood. Extensive computational results on standard benchmark instances show the effectiveness of the approach with respect to exact and heuristic algorithms from the literature. (C) 2002 Elsevier Science B.V. All rights reserved.
Number partitioning is a classic problem in artificial intelligence. And balanced multi-way number partitioning problem (BMNP) aims to partition a set of numbers into multiple subsets, such that (1) each subset contai...
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Number partitioning is a classic problem in artificial intelligence. And balanced multi-way number partitioning problem (BMNP) aims to partition a set of numbers into multiple subsets, such that (1) each subset contains the same number of numbers and (2) the subset sums are equal. The BMNP problem has various applications in real world scenarios, including task allocation, CPU scheduling, file placement in data center, multi-source data processing, etc. In this paper, we consider the problem of diversity-aware balanced multi-way number partitioning (DBMNP). DBMNP differs from BMNP, in that each number is associated with a type attribute. In addition to the two goals of BMNP, DBMNP also requires that the types of numbers in each subset are as diversified as possible. To solve the problem, we propose three heuristic algorithms to minimize the difference between subset sums and at the same time maximize diversify of each subset. Extensive experiments are conducted to evaluate the effectiveness of our proposed algorithms. (C) 2020 Elsevier B.V. All rights reserved.
This study suggests an approach that synchronizes timing points found between a supplier and a buyer in a serial supply chain with one in two timing points to allow for more efficient and agile material flow. This app...
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This study suggests an approach that synchronizes timing points found between a supplier and a buyer in a serial supply chain with one in two timing points to allow for more efficient and agile material flow. This approach is applied to the problem of finding an optimal solution for the production quantity in each production lot and the job sequence with minimum supply chain total cost and lead time. Five heuristic algorithms were developed based on simulated annealing (SA) and a genetic algorithm (GA). Of the developed heuristic algorithms, GA2 exhibited the most robustness. (C) 2009 Elsevier B.V. All rights reserved.
Residential HVAC control is a large untapped resource for providing regulation services to the grid. This paper presents a set of algorithms for controlling HVACs of a group of residential houses that a demand respons...
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Residential HVAC control is a large untapped resource for providing regulation services to the grid. This paper presents a set of algorithms for controlling HVACs of a group of residential houses that a demand response aggregator can use to sell regulation service in the wholesale market. The focus is on the regulation market offered by the PJM RTO. Real-world regulation signals from PJM are used to simulate the performance and range of regulation services in a realistic scenario. After presenting the empirical counter example for why a universal optimal control strategy cannot exist for regulation, a set of heuristic algorithms is presented, which performs well in a range of test cases. The control mechanism involves a central controller communicating with smart thermostats of multiple residential houses to gather indoor temperature data, prioritizing them according to certain heuristics and sending on/off signals back to the thermostats to control the HVAC. The case studies indicate that the proposed heuristic algorithms can deliver the required regulation services, while adequately handling communication delays, different types of regulation signals and household's thermal comfort requirements.
Waste load allocation for rivers has been a topic of growing interest. Dynamic programming based algorithms are particularly attractive in this context and are widely reported in the literature. Codes developed for dy...
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Waste load allocation for rivers has been a topic of growing interest. Dynamic programming based algorithms are particularly attractive in this context and are widely reported in the literature. Codes developed for dynamic programming are however complex, require substantial computer resources and importantly do not allow interactions of the user. Further, there is always resistance to utilizing mathematical programming based algorithms for practical applications. There has been therefore always a gap between theory and practice in systems analysis in water quality management. This paper presents various heuristic algorithms to bridge this gap with supporting comparisons with dynamic programming based algorithms. These heuristics make a good use of the insight gained in the system's behaviour through experience, a process akin to the one adopted by field personnel and therefore can readily be understood by a user familiar with the system. Also they allow user preferences in decision making via on-line interaction. Experience has shown that these heuristics are indeed well founded and compare very favourably with the sophisticated dynamic programming algorithms. Two examples have been included which demonstrate such a success of the heuristic algorithms.
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