Mohammadreza Dabiri; Mehdi Yazdani; bahman naderi; Hasan Haleh
Abstract
In the real world, firms with hybrid flow-shop manufacturing environment generally facethe human resource constraint, salary cost increasment and efforts to make better use oflabor, in addition to machine constraint. Given the limitations of these resources, productdelivery requierements to customers ...
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In the real world, firms with hybrid flow-shop manufacturing environment generally facethe human resource constraint, salary cost increasment and efforts to make better use oflabor, in addition to machine constraint. Given the limitations of these resources, productdelivery requierements to customers have made the job rejection essential in order to meetdistinct customer requirements. Therefore, this research has studied the dual resourceconstrained hybrid flow-shop scheduling problem with job rejection in order to minimizethe total net cost (the sum of the total rejection cost and the total tardiness cost of jobs)which is widely used in many industries. In this article, a mixed integer linear programmingmodel has developed for the research problem. In addition, an improved sooty ternoptimization algorithm (ISTOA) has proposed to solve the large-sized problems as well asa decoding method due to the NP-hardness of the problem. In order to evaluate theproposed optimization algorithm, five well-known algorithms in the literature including(immunoglobulin-based artificial immune system (IAIS), genetic algorithm (GA), discreteartificial bee colony (DABC), improved fruit fly optimization (IFFO), effective modifiedmigrating birds optimization (EMBO)) have adapted with the proposed problem. Finally,the performance of the proposed optimization algorithm has investigated against theadapted algorithms. Results and evaluations show the good performance of the improvedsooty tern optimization algorithm.
Abstract
One of the most important problems of logistic networks is designing and analyzing of the distribution network. The design of distribution systems raises hard combinatorial optimization problems. In recent years, two main problems in the design of distribution networks that are location of distribution ...
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One of the most important problems of logistic networks is designing and analyzing of the distribution network. The design of distribution systems raises hard combinatorial optimization problems. In recent years, two main problems in the design of distribution networks that are location of distribution centres and routing of distributors are considered together and created the location-routing problem. The location-routing problem (LRP), integrates the two kinds of decisions. The classical LRP, consists in opening a subset of depots, assigning customers to them and determining vehicle routes, to minimize total cost of the problem. In this paper, a dynamic capacitated location-routing problem is considered that there are a number of potential depot locations and customers with specific demand and locations, and some vehicles with a certain capacity. Decisions concerning facility locations are permitted to be made only in the first time period of the planning horizon but, the routing decisions may be changed in each time period. In this study, customer demands depend on the products offering prices. The corresponding model and presented results related to the implementation of the model by different solution methods have been analysed by different methods. A hybrid heuristic algorithm based on particle swarm optimization is proposed to solve the problem. To evaluate the performance of the proposed algorithm, the proposed algorithm results are compared with exact algorithm optimal value and lower bounds. The comparison between hybrid proposed algorithm and exact solutions are performed and computational experiments show the effectiveness of the proposed algorithm.
Seyed Mohammad Taghi Fatemi Ghomi; Ehsan Arabzadeh; Behrooz Karimi
Abstract
Home health care services have a key importance in modern societies. Most organizations working in this area in Iran use the traditional procedure to plan and manage medical staff and determine the arrangement of visiting patients. This procedure often increases costs and reduces the satisfaction of ...
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Home health care services have a key importance in modern societies. Most organizations working in this area in Iran use the traditional procedure to plan and manage medical staff and determine the arrangement of visiting patients. This procedure often increases costs and reduces the satisfaction of patients. In this paper, a multi-period routing and scheduling model is proposed in order to visit patients and provide them medical services. Considering both dependency and independence of a patient's visits with each other, assuming the model as multi-depot as well as multi period are some innovations of this study. The main purpose of the proposed model is to reduce total costs of home health care organization. Model has been solved in small scale by GAMS software. To solve the model in large scale, developed Variable neighborhood search is proposed and compared with simulated annealing algorithm and ant colony system. Results show that costs are decreased and the proposed algorithm has better performance
Maghsoud Amiri; Mahdi Keshavarz Gharabaei
Volume 13, Issue 36 , April 2015, , Pages 143-171
Abstract
Actual scheduling problems may necessitate the decision maker to consider a variety of criteria prior to make any decision. This research considers a single machine scheduling problem, with the objective of minimizing a combination of total tardiness and waiting time variance criteria in which the idle ...
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Actual scheduling problems may necessitate the decision maker to consider a variety of criteria prior to make any decision. This research considers a single machine scheduling problem, with the objective of minimizing a combination of total tardiness and waiting time variance criteria in which the idle time is not allowed. Minimizing total tardiness is always regarded as one of the most important performance criteria in practical systems to avoid penalty costs of tardiness and waiting time variance is an important criterion in establishing Quality of Service (QoS) in many systems. Each of these criteria is known to be NP-hard and therefore the linear combination of them will be NP-hard as well. For this problem, we developed a genetic algorithm by utilizing its general structure. Two types of heuristic and random initial population and two distinct fitness functions are applied to genetic algorithms. The GA is shown experimentally to perform well by testing on various instances.
