Computational Management Science最新文献_第2页

A refinement of the gravity model for competitive facility location 竞争性设施选址重力模型的改进

Computational Management Science Pub Date : 2023-11-02 DOI: 10.1007/s10287-023-00484-w

Zvi Drezner, Dawit Zerom

引用次数: 0

Emergency exit layout planning using optimization and agent-based simulation 基于优化和智能体仿真的紧急出口布局规划

Computational Management Science Pub Date : 2023-10-30 DOI: 10.1007/s10287-023-00482-y

Maren S. Barth, Katharina Palm, Henrik Andersson, Tobias A. Granberg, Anders N. Gullhav, Andreas Krüger

{"title":"Emergency exit layout planning using optimization and agent-based simulation","authors":"Maren S. Barth, Katharina Palm, Henrik Andersson, Tobias A. Granberg, Anders N. Gullhav, Andreas Krüger","doi":"10.1007/s10287-023-00482-y","DOIUrl":"https://doi.org/10.1007/s10287-023-00482-y","url":null,"abstract":"Abstract Evacuation preparedness includes ensuring proper infrastructure, resources and planning for moving people from a dangerous area to safety. This is especially important and challenging during mass gatherings, such as large concerts. In this paper, we present the Emergency Exit Layout Problem (EELP) which is the problem of locating a given number of emergency exits and deciding their width such that the time it takes to evacuate the crowd from an arena is minimized. The EELP takes into account the geography of the arena and its surroundings, as well as the number of pedestrians in the crowd and the distribution of these within the arena. The EELP is formulated as a two-stage stochastic mixed integer linear program to handle the uncertainty related to the location of the possible incidents and the distribution of the pedestrians. Two cases are studied, a large concert planned at the Leangen trotting track in Trondheim and a smaller indoor arena. For each case, the EELP is solved for different scenarios, and the suggested layouts are evaluated using an agent-based simulation model. In particular, the potential of incorporating detailed assessment regarding the location and probability of specific incidents and the distribution of pedestrians are investigated. The computational study shows that making a more detailed risk assessment has little effect on the large concert, but a significant impact on the location of the emergency exits for the smaller indoor case. The results also indicate that it is more important to consider the location and probability of specific incidents rather than the pedestrian distribution.","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"32 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136104148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Non-smooth setting of stochastic decentralized convex optimization problem over time-varying Graphs 时变图随机分散凸优化问题的非光滑设置

Computational Management Science Pub Date : 2023-10-24 DOI: 10.1007/s10287-023-00479-7

Aleksandr Lobanov, Andrew Veprikov, Georgiy Konin, Aleksandr Beznosikov, Alexander Gasnikov, Dmitry Kovalev

引用次数: 2

Integration of inventory control, maintenance policy, and quality control for selling products under warranty 整合库存控制、维修政策和质量控制，销售保修期内的产品

Computational Management Science Pub Date : 2023-10-18 DOI: 10.1007/s10287-023-00481-z

Ali Salmasnia, Soudabeh Hajihaji, Saeid Sharafi, Mohammad Reza Maleki

引用次数: 0

Wrong Way Risk corrections to CVA in CIR reduced-form models 在CIR简化模型中对CVA的风险修正

Computational Management Science Pub Date : 2023-10-16 DOI: 10.1007/s10287-023-00480-0

Fabio Antonelli, Alessandro Ramponi, Sergio Scarlatti

引用次数: 0

Preference robust state-dependent distortion risk measure on act space and its application in optimal decision making 行为空间上的偏好鲁棒状态相关失真风险测度及其在最优决策中的应用

Computational Management Science Pub Date : 2023-10-05 DOI: 10.1007/s10287-023-00475-x

Wei Wang, Huifu Xu

引用次数: 0

An ALNS-based matheuristic algorithm for a multi-product many-to-many maritime inventory routing problem 多产品多对多海运库存调度问题的基于alns的数学算法

Computational Management Science Pub Date : 2023-09-30 DOI: 10.1007/s10287-023-00478-8

Nooshin Heidari, Ahmad Hemmati

{"title":"An ALNS-based matheuristic algorithm for a multi-product many-to-many maritime inventory routing problem","authors":"Nooshin Heidari, Ahmad Hemmati","doi":"10.1007/s10287-023-00478-8","DOIUrl":"https://doi.org/10.1007/s10287-023-00478-8","url":null,"abstract":"Abstract In this paper, we propose an adaptive large neighborhood search-based matheuristic algorithm to solve a multi-product many-to-many maritime inventory routing problem. The problem addresses a short sea inventory routing problem that aims to find the best route and distribution plan for multiple products with a heterogeneous fleet of vessels through a network including several producers and customers. Each port can be visited a given number of times during the planning horizon, and the stock level for each product should lie within the predefined bound limits. The problem was introduced by Hemmati et al. (Eur J Oper Res 252:775–788, 2016). They developed a mixed integer programming formulation and proposed a matheuristic algorithm to solve the problem. Although their proposed algorithm worked well in terms of running time, it suffers from disregarding a part of the solution space. In this study, we propose a new matheuristic algorithm to find better solutions by exploring the entire solution space for the same problem. In our solution methodology, we split the variables into routing and non-routing variables. Then in an iterative process, we determine the values of the routing variables with an adaptive large neighborhood search algorithm, and we pass them as input to a penalized model which is a relaxed and modified version of the mathematical model introduced in Hemmati et al. (2016). The information from solving the penalized model, including the values of the non-routing variables, is then passed to the adaptive large neighborhood search algorithm for the next iteration. Several problem-dependent operators are defined. The operators use the information they get from the penalized model and focus on decreasing the penalty values. Computational results show up to 26% improvement in the quality of the solutions for the group of instances with a large feasible solution space. We get the optimal value for the remaining instances matched with the reported results.","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136279937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Approximate variational inequalities and equilibria 近似变分不等式和均衡

Computational Management Science Pub Date : 2023-09-25 DOI: 10.1007/s10287-023-00476-w

Giancarlo Bigi, Lorenzo Lampariello, Simone Sagratella, Valerio Giuseppe Sasso

引用次数: 1

On efficiency and the Jain’s fairness index in integer assignment problems 整数分配问题的效率与Jain公平性指标

Computational Management Science Pub Date : 2023-09-22 DOI: 10.1007/s10287-023-00477-9

Nahid Rezaeinia, Julio C. Góez, Mario Guajardo

{"title":"On efficiency and the Jain’s fairness index in integer assignment problems","authors":"Nahid Rezaeinia, Julio C. Góez, Mario Guajardo","doi":"10.1007/s10287-023-00477-9","DOIUrl":"https://doi.org/10.1007/s10287-023-00477-9","url":null,"abstract":"Abstract Given two sets of objects, the integer assignment problem consists of assigning objects of one set to objects in the other set. Traditionally, the goal of this problem is to find an assignment that minimizes or maximizes a measure of efficiency, such as maximization of utility or minimization of cost. Lately, the interest in incorporating a measure of fairness in addition to efficiency has gained importance. This paper studies how to incorporate these two criteria in an integer assignment, using the Jain’s index as a measure of fairness. The original formulation of the assignment problem with this index involves a non-concave function, which renders a non-linear non-convex problem, usually hard to solve. To this aim, we develop two reformulations, where one is based on a quadratic objective function and the other one is based on integer second-order cone programming. We explore the performance of these reformulations in instances of real-world data derived from an application of assigning personnel to projects, and also in instances of randomly generated data. In terms of solution quality, all formulations prove to be effective in finding solutions capturing both efficiency and fairness criteria, with some slight differences depending on the type of instance. In terms of solving time, however, the performances of the formulations differ considerably. In particular, the integer quadratic approach proves to be much faster in finding optimal solutions.","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136060071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Renewable electricity capacity planning with uncertainty at multiple scales 具有多个规模不确定性的可再生电力容量规划

IF 0.9

Computational Management Science Pub Date : 2023-09-08 DOI: 10.1007/s10287-023-00472-0

M. Ferris, Andrew B. Philpott

引用次数: 0