penalty costs
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2021 ◽  
Author(s):  
Jesús Manuel Núñez-López ◽  
Brenda Cansino-Loeza ◽  
Xaté Geraldine Sánchez Zarco ◽  
José María Ponce-Ortega

Abstract The proper planning of the water-energy-food nexus is key for urban sustainability. However, the security of water, energy, and food is posed at risk due to uncertain events such as natural disasters. The quantification of resilience in water-energy-food systems has gained relevance in recent years and has served as a key tool to identify vulnerable areas. This work presents a systematic approach to assessing the resilience of the water-energy-food nexus in arid/semiarid regions that present low availability of resources. A methodology for assessing the resilience of the water-energy-food nexus of an arid region is presented, which allows evaluating the system under the disturbances of natural disasters such as hurricanes, low-temperature events, and droughts. The events in which failures in functional services may occur are analyzed using penalty costs. To apply the proposed approach, scenarios corresponding to past conditions and future projections were evaluated for two Mexican arid cities. The results show that it is possible to identify vulnerable areas related to the existence of natural disasters and thereby look for alternatives to maintain the security of the nexus. The proposed approach is general, and it can be applied to other regions with similar characteristics.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rodolfo Benedito Zattar da Silva ◽  
Flávio Sanson Fogliatto ◽  
André Krindges ◽  
Moiseis dos Santos Cecconello

Abstract Background We propose a mathematical model formulated as a finite-horizon Markov Decision Process (MDP) to allocate capacity in a radiology department that serves different types of patients. To the best of our knowledge, this is the first attempt at considering radiology resources with different capacities and individual no-show probabilities of ambulatory patients in an MDP model. To mitigate the negative impacts of no-show, overbooking rules are also investigated. Methods The model’s main objective is to identify an optimal policy for allocating the available capacity such that waiting, overtime, and penalty costs are minimized. Optimization is carried out using traditional dynamic programming (DP). The model was applied to real data from a radiology department of a large Brazilian public hospital. The optimal policy is compared with five alternative policies, one of which resembles the one currently used by the department. We identify among alternative policies the one that performs closest to the optimal. Results The optimal policy presented the best performance (smallest total daily cost) in the majority of analyzed scenarios (212 out of 216). Numerical analyses allowed us to recommend the use of the optimal policy for capacity allocation with a double overbooking rule and two resources available in overtime periods. An alternative policy in which outpatients are prioritized for service (rather than inpatients) displayed results closest to the optimal policy, being also recommended due to its easy implementation. Conclusions Based on such recommendation and observing the state of the system at any given period (representing the number of patients waiting for service), radiology department managers should be able to make a decision (i.e., define number and type of patients) that should be selected for service such that the system’s cost is minimized.


2021 ◽  
Author(s):  
Wullapa Wongsinlatam ◽  
Ayuwat Thanasate-angkool

Abstract The study of sustainable management of municipal solid waste (MSW) collection has been increasing in recent years. However, the focus areas of research are mostly in the economics and environmental dimensions. This paper adds social aspects of MSW into considerations to accelerate more comprehensive decision making. The consideration on the capacity and fixed costs of vehicles, the distances from depot to the disposal facilities are determined in this paper. The environmental issues relating to fuel consumption, carbon emissions, and the evaluation of social impact from the penalty costs of imbalanced trip assignments are also determined to adopt a comprehensive solution to the capacitated vehicle routing problem (CVRP) model. Then, the optimization model of MSW collection is proposed to minimize management costs which compose of the fixed costs of vehicles, fuel consumption costs, carbon emissions costs, and penalty costs. In this paper, two metaheuristic techniques are used to optimization the CVRP model in the MSW collection system. A new metaheuristic algorithm, called an intelligence hybrid harmony search algorithm (IHHS), is proposed in comparison with the standard harmony search (SHS) algorithm. The result shows that the IHHS algorithm can obtain the global optimal solution and can minimize the total objective function for the CVRP model.


2021 ◽  
Author(s):  
Yohan Jeju John

Many organizations are faced with a decision to choose between two inventory systems namely JIT (Just in Time) and EOQ (Economic Order Quantity). This thesis models the cost drivers into the EOQ model and extends it to the JIT scenario. They include cost savings like space, synergy of coordination, and other cost factors like rework and penalty costs. It looks at the total cost of the supply chain with two players and calculates space in terms of storage spaces of equal capacity. Results showed that considering space in EOQ brought savings to the chain. It has brought down the order quantity closer to, and many times equal to JIT ordering quantities. Coordination in the chain has brought further savings. Moving to JIT (ordering daily supply of demand) from the point, where space is accounted and there is coordination between the two levels, did not require much reduction in ordering costs.


2021 ◽  
Author(s):  
Yohan Jeju John

Many organizations are faced with a decision to choose between two inventory systems namely JIT (Just in Time) and EOQ (Economic Order Quantity). This thesis models the cost drivers into the EOQ model and extends it to the JIT scenario. They include cost savings like space, synergy of coordination, and other cost factors like rework and penalty costs. It looks at the total cost of the supply chain with two players and calculates space in terms of storage spaces of equal capacity. Results showed that considering space in EOQ brought savings to the chain. It has brought down the order quantity closer to, and many times equal to JIT ordering quantities. Coordination in the chain has brought further savings. Moving to JIT (ordering daily supply of demand) from the point, where space is accounted and there is coordination between the two levels, did not require much reduction in ordering costs.


2021 ◽  
Vol 9 (5) ◽  
pp. 527
Author(s):  
Armi Kim ◽  
Hyun-Ji Park ◽  
Jin-Hyoung Park ◽  
Sung-Won Cho

The rapid increase in international trade volume has caused frequent fluctuation of the vessels’ arrival time in container terminals. In order to solve this problem, this study proposes a methodology for rescheduling berth and quay cranes caused by updated information on the arrival time of vessels. A mixed-integer linear programming model was formulated for the berth allocation and crane assignment problem, and we solved the problem using a rolling-horizon approach. Numerical experiments were conducted under three scenarios with empirical data from a container terminal located in Busan, Korea. The experiments revealed that the proposed model reduces penalty costs and overall delayed departure time compared to the results of the terminal planner.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Zhaohui Gao ◽  
Caiyun Ye

In the reverse logistics recycling process, considering the diversity of recycling types, a variety of vehicle models are used to meet the reverse logistics recycling requirements. Therefore, this paper considers the fixed costs, transportation costs, carbon emission costs during driving, and time penalty costs in the reverse logistics process under multiple constraints such as multiple vehicle types and time windows in the recycling center. The recovery point is the recovery model, and an improved genetic algorithm is used to solve it. Drawing lessons from the idea of greed, the superiority of the initial population is improved; the entry matrix and the exit matrix of the iterative population are constructed, and the crossover operator is improved based on this, and the forward insertion method is introduced to design the hybrid crossover operation to speed up the population. At the same time, the improvement of the mutation operator is proposed to increase the diversity of the population. The experimental results show that the multivehicle mixed delivery mode can reduce costs more effectively than single-vehicle models, and the improved genetic algorithm has better convergence and stability.


Author(s):  
Myoung-Ju Park ◽  
Byung-Cheon Choi ◽  
Jibok Chung

We consider two variants of a time–cost tradeoff problem with multiple assessments on a chain precedence graph. Furthermore, each job can only be started after a release time, and a penalty cost is incurred when a job is not finished before its due date. The motivation is from the project such that a project owner can control the duration of each job and the support level of each project partner to avoid the penalty cost from the tardy jobs. We describe the penalty costs of the first and the second variants as the total weighted number of tardy jobs and the total weighted tardiness, respectively. These can be avoided by compressing the processing times or advancing the release times, which incurs a compression cost or release cost according to the linear and the piecewise constant functions, respectively. The objective is to minimize the total penalty, compression cost and release cost. In this paper, we propose the procedure based on the reduction to a shortest path problem, and show that the procedure can solve two variants in strongly polynomial time.


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