PolyU IR Collection:
http://hdl.handle.net/10397/69
2015-07-25T18:19:03ZStudy on the recycling and treatment of WEEE in China
http://hdl.handle.net/10397/6960
Title: Study on the recycling and treatment of WEEE in China
Authors: Yang, Bibo; Chen, Renxia
Abstract: This paper investigates the regulations, recycling and treatment of WEEE (waste electrical and electronic equipment) in China. An online survey about Chinese households’ treatment of WEEE is conducted. Optimization models are used to compare the performances of WEEE treatment in two different recycling networks. In the first network, WEEE is collected and sent by recycling stations to licensed WEEE recycling and treatment centers for testing and dismantling. In the second network, WEEE are tested and dismantled at small recycling workshops in residential districts, and then parts/components that require further processing are sent to licensed WEEE recycling and treatment centers. The performances of the two networks are analyzed with linear programming models. The results indicate that the second model is more effective with lower cost and higher recycling efficiency.2012-09-01T00:00:00ZSome properties of multiple parameters linear programming
http://hdl.handle.net/10397/6529
Title: Some properties of multiple parameters linear programming
Authors: Li, Maoqin; Li, Shanlin; Yan, Hong
Abstract: We consider a linear programming problem in which the right-hand side vector depends on multiple parameters. We study the characters of the optimal value function and the critical regions based on the concept of the optimal partition. We show that the domain of the optimal value function f can be decomposed into finitely many subsets with disjoint relative interiors, which is different from the result based on the concept of the optimal basis. And any directional derivative of f at any point can be computed by solving a linear programming problem when only an optimal solution is available at the point.2010-06-28T00:00:00ZBicriterion single machine scheduling with resource dependent processing times
http://hdl.handle.net/10397/6037
Title: Bicriterion single machine scheduling with resource dependent processing times
Authors: Cheng, T. C. Edwin; Janiak, Adam; Kovalyov, Mikhail Y.
Abstract: A bicriterion problem of scheduling jobs on a single machine is studied. The processing time of each job is a linear decreasing function of the amount of a common discrete resource allocated to the job. A solution is specified by a sequence of the jobs and a resource allocation. The quality of a solution is measured by two criteria, F₁ and F₂. The first criterion is the maximal or total (weighted) resource consumption, and the second criterion is a regular scheduling criterion depending on the job completion times. Both criteria have to be minimized. General schemes for the construction of the Pareto set and the Pareto set ϵ-approximation are presented. Computational complexities of problems to minimize F₁ subject to F₂ ≤ K and to minimize F₂ subject to F₁≤ K, where K is any number, are studied for various functions F₁ and F₂. Algorithms for solving these problems and for the construction of the Pareto set and the Pareto set ϵ-approximation for the corresponding bicriterion problems are presented.1998-05-01T00:00:00ZSingle machine scheduling to minimize batch delivery and job earliness penalties
http://hdl.handle.net/10397/6036
Title: Single machine scheduling to minimize batch delivery and job earliness penalties
Authors: Cheng, T. C. Edwin; Kovalyov, Mikhail Y.; Lin, Bertrand M.-T.
Abstract: We study a problem in which a set of n jobs has to be batched as well as scheduled for processing on a single machine. A constant machine set-up time is required before the first job of each batch is processed. A schedule specifies the sequence of batches, where each batch comprises a sequence of jobs. The batch delivery time is defined as the completion time of the last job in a batch. The earliness of a job is defined as the difference between the delivery time of the batch to which it belongs and the job completion time. The objective is to find a number B of batches and a schedule so as to minimize the sum of the total weighted job earliness and mean batch delivery time. The problem is shown to be strongly NP-hard. It remains strongly NP-hard if the set-up time is zero and B ≤ U for any variable U ≥ 2 or if B ≥ U for any constant U ≥ 2. The problem is proved to be ordinary NP-hard even if the set-up time is zero and B ≤ 2. For the case B ≤ U, a dynamic programming algorithm is presented, which is pseudopolynomial for any constant U ≥ 2. Algorithms with O(n²) running times are derived for the cases when all weights are equal or all processing times are equal. For the general problem, a family of heuristics is suggested. Computational experiments on the proposed heuristic algorithm are conducted. The results suggest that the heuristics are effective in generating near-optimal solutions quickly.1997-05-01T00:00:00Z