scholarly journals A Bi-level Decomposition Algorithm for Multi-factory Scheduling With Batch Delivery Problem

2022 ◽  
Author(s):  
Fateme Marandi ◽  
S.M.T. Fatemi Ghomi
Keyword(s):  
Programming Model ◽  
Real Life ◽  
Decomposition Algorithm ◽  
Mixed Integer ◽  
Delivery Problem ◽  
Batch Delivery ◽  
Upper Level ◽  
Factory Scheduling ◽  
Short Time ◽  
Zinc Industry

Abstract This paper introduces a multi-factory scheduling with batch delivery problem. A novel mixed-integer programming model is proposed to minimize the sum of total tardiness, holding and batching costs. A bi-level decomposition algorithm (BLDA) is developed involving two sub-problems: scheduling problem in the upper level and batching problem in the lower level. Four versions of the BLDA are created by combinations of CPLEX and simulated annealing in both levels, which interactively collaborate until the algorithm converges to a solution. The BLDAs are examined on several random and real-life test instances. A statistical analysis is performed by comparing the BLDAs’ solutions with the exact minimum and lower bound values of the total cost. The results indicate that about all versions of the developed BLDA provide high quality solutions for real-world zinc industry problems as well as generated instances in a reasonably short time. Finally, some managerial insights are derived based on sensitivity analysis.

scholarly journals A Generalized Minimum Cost Flow Model for Multiple Emergency Flow Routing

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jianxun Cui ◽  
Shi An ◽  
Meng Zhao
Keyword(s):  
Flow Model ◽  
Time Window ◽  
Programming Model ◽  
Real Life ◽  
Minimum Cost ◽  
Emergency Evacuation ◽  
Mixed Integer ◽  
Fixed Cost ◽  
Minimum Cost Flow ◽  
Cost Flow

During real-life disasters, that is, earthquakes, floods, terrorist attacks, and other unexpected events, emergency evacuation and rescue are two primary operations that can save the lives and property of the affected population. It is unavoidable that evacuation flow and rescue flow will conflict with each other on the same spatial road network and within the same time window. Therefore, we propose a novel generalized minimum cost flow model to optimize the distribution pattern of these two types of flow on the same network by introducing the conflict cost. The travel time on each link is assumed to be subject to a bureau of public road (BPR) function rather than a fixed cost. Additionally, we integrate contraflow operations into this model to redesign the network shared by those two types of flow. A nonconvex mixed-integer nonlinear programming model with bilinear, fractional, and power components is constructed, and GAMS/BARON is used to solve this programming model. A case study is conducted in the downtown area of Harbin city in China to verify the efficiency of proposed model, and several helpful findings and managerial insights are also presented.

A solution method for treatment scheduling in rehabilitation hospitals with real-life requirements

2018 ◽  
Vol 30 (4) ◽  
pp. 367-386 ◽  
Author(s):  
Liyang Xiao ◽  
Mahjoub Dridi ◽  
Amir Hajjam El Hassani ◽  
Wanlong Lin ◽  
Hongying Fei
Keyword(s):  
Waiting Time ◽  
Programming Model ◽  
Search Algorithm ◽  
Real Life ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Mixed Integer ◽  
Solution Quality ◽  
Improved Cuckoo Search Algorithm ◽  
Rehabilitation Hospitals

Abstract In this study, we aim to minimize the total waiting time between successive treatments for inpatients in rehabilitation hospitals (departments) during a working day. Firstly, the daily treatment scheduling problem is formulated as a mixed-integer linear programming model, taking into consideration real-life requirements, and is solved by Gurobi, a commercial solver. Then, an improved cuckoo search algorithm is developed to obtain good quality solutions quickly for large-sized problems. Our methods are demonstrated with data collected from a medium-sized rehabilitation hospital in China. The numerical results indicate that the improved cuckoo search algorithm outperforms the real schedules applied in the targeted hospital with regard to the total waiting time of inpatients. Gurobi can construct schedules without waits for all the tested dataset though its efficiency is quite low. Three sets of numerical experiments are executed to compare the improved cuckoo search algorithm with Gurobi in terms of solution quality, effectiveness and capability to solve large instances.

scholarly journals Emission-Intensity-Based Carbon Tax and Its Impact on Generation Self-Scheduling

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 777 ◽  
Author(s):  
Ping Che ◽  
Yanyan Zhang ◽  
Jin Lang
Keyword(s):  
Electricity Market ◽  
Emission Intensity ◽  
Tax Policy ◽  
Programming Model ◽  
Carbon Tax ◽  
Electric Power Industry ◽  
Decomposition Algorithm ◽  
Mixed Integer ◽  
Tax Rate ◽  
The Impact

We propose an emission-intensity-based carbon-tax policy for the electric-power industry and investigate the impact of the policy on thermal generation self-scheduling in a deregulated electricity market. The carbon-tax policy is designed to take a variable tax rate that increases stepwise with the increase of generation emission intensity. By introducing a step function to express the variable tax rate, we formulate the generation self-scheduling problem under the proposed carbon-tax policy as a mixed integer nonlinear programming model. The objective function is to maximize total generation profits, which are determined by generation revenue and the levied carbon tax over the scheduling horizon. To solve the problem, a decomposition algorithm is developed where the variable tax rate is transformed into a pure integer linear formulation and the resulting problem is decomposed into multiple generation self-scheduling problems with a constant tax rate and emission-intensity constraints. Numerical results demonstrate that the proposed decomposition algorithm can solve the considered problem in a reasonable time and indicate that the proposed carbon-tax policy can enhance the incentive for generation companies to invest in low-carbon generation capacity.

scholarly journals A hybrid meta-heuristics approach for supplier selection and order allocation problem for supplying risks of recyclable raw materials

2021 ◽  
pp. 177-190 ◽  
Author(s):  
Nguyen Hoang Son ◽  
Nguyen Van Hop
Keyword(s):  
Supplier Selection ◽  
Programming Model ◽  
Raw Materials ◽  
Real Life ◽  
Optimal Solution ◽  
Allocation Problem ◽  
Mixed Integer ◽  
Order Allocation ◽  
Supply Risks ◽  
The Right

In this work, a mixed-integer linear programming model is formulated to allocate the appropriate orders to the right suppliers for recyclable raw materials. We modify the previous model for the supplier selection and order allocation problem for stochastic demand to cope with the supply risks of recyclable raw materials such as insufficient supply quantity, defective rate, and late delivery. The optimal solution of the mathematical model is the benchmark for small-sized problems. Then, a hybrid meta-heuristic of Particles Swarm Optimization and Grey Wolf Optimization (PSO-GWO) is proposed to search for the best solution for large-sized problems. A real-life case study of a steel manufacturer with two factories in Vietnam is presented to validate the proposed approach. Some experiments have been tested to confirm the performance of the hybrid PSO-GWO approach.

scholarly journals Linear programming problems with some multi-choice fuzzy parameters

2018 ◽  
Vol 28 (2) ◽  
pp. 249-264 ◽  
Author(s):  
Avik Pradhan ◽  
Biswal Prasad
Keyword(s):  
Linear Programming ◽  
Fuzzy Numbers ◽  
Programming Model ◽  
Real Life ◽  
Optimal Solution ◽  
Linear Programming Model ◽  
Mixed Integer ◽  
Non Linear Programming ◽  
A Value ◽  
Linear Programming Problems

In this paper, we consider some Multi-choice linear programming (MCLP) problems where the alternative values of the multi-choice parameters are fuzzy numbers. There are some real-life situations where we need to choose a value for a parameter from a set of different choices to optimize our objective, and those values of the parameters can be imprecise or fuzzy. We formulate these situations as a mathematical model by using some fuzzy numbers for the alternatives. A defuzzification method based on incentre point of a triangle has been used to find the defuzzified values of the fuzzy numbers. We determine an equivalent crisp multi-choice linear programming model. To tackle the multi-choice parameters, we use Lagranges interpolating polynomials. Then, we establish a transformed mixed integer nonlinear programming problem. By solving the transformed non-linear programming model, we obtain the optimal solution for the original problem. Finally, two numerical examples are presented to demonstrate the proposed model and methodology.

scholarly journals Integrated Production-Distribution Scheduling Problem with Multiple Independent Manufacturers

2015 ◽  
Vol 2015 ◽  
pp. 1-5 ◽  
Author(s):  
Jianhong Hao ◽  
Lisi Cao ◽  
Dakui Jiang
Keyword(s):  
Public Service ◽  
Parallel Machines ◽  
Programming Model ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Production Schedule ◽  
Integrated Production ◽  
Batch Delivery ◽  
Distribution Scheduling ◽  
Production Distribution

We consider the nonstandard parts supply chain with a public service platform for machinery integration in China. The platform assigns orders placed by a machinery enterprise to multiple independent manufacturers who produce nonstandard parts and makes production schedule and batch delivery schedule for each manufacturer in a coordinate manner. Each manufacturer has only one plant with parallel machines and is located at a location far away from other manufacturers. Orders are first processed at the plants and then directly shipped from the plants to the enterprise in order to be finished before a given deadline. We study the above integrated production-distribution scheduling problem with multiple manufacturers to maximize a weight sum of the profit of each manufacturer under the constraints that all orders are finished before the deadline and the profit of each manufacturer is not negative. According to the optimal condition analysis, we formulate the problem as a mixed integer programming model and use CPLEX to solve it.

scholarly journals A MATHEMATICAL MODEL FOR DYNAMIC PROJECT SCHEDULING PROBLEM AND REACTIVE SCHEDULING IMPLEMENTATION

2020 ◽  
Vol 8 (4) ◽  
pp. 83-97
Author(s):  
Murat RUHLUSARAÇ ◽  
Filiz ÇALIŞKAN
Keyword(s):  
Project Scheduling ◽  
Resource Constraints ◽  
Programming Model ◽  
Real Life ◽  
Dynamic Environment ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Baseline Schedule ◽  
Dynamic Events ◽  
Project Scheduling Problem

In today's real-life implementations, projects are executed under uncertainty in a dynamic environment. In addition to resource constraints, the baseline schedule is affected due to the unpredictability of the dynamic environment. Uncertainty-based dynamic events experienced during project execution may change the baseline schedule partially or substantially and require projects' rescheduling. In this study, a mixed-integer linear programming model is proposed for the dynamic resource-constrained project scheduling problem. Three dynamic situation scenarios are solved with the proposed model, including machine breakdown, worker sickness, and electricity power cut. Finally, generated reactive schedules are completed later than the baseline schedule.

scholarly journals Mathematical Model and Stochastic Multi-Criteria Acceptability Analysis for Facility Location Problem

2016 ◽  
Vol 28 (3) ◽  
pp. 245-256 ◽  
Author(s):  
Selahattin Karabay ◽  
Erkan Köse ◽  
Mehmet Kabak ◽  
Eren Ozceylan
Keyword(s):  
Mathematical Programming ◽  
Facility Location ◽  
Location Problem ◽  
Programming Model ◽  
Real Life ◽  
Facility Location Problem ◽  
Mixed Integer ◽  
Mathematical Programming Model ◽  
General Management ◽  
New Facilities

This paper studies a real-life public sector facility location problem. The problem fundamentally originated from the idea of downsizing the number of service centres. However, opening of new facilities is also considered in case the current facilities fail to fulfil general management demands. Two operation research methodologies are used to solve the problem and the obtained results are compared. First, a mathematical programming model is introduced to determine where the new facilities will be located, and which districts get service from which facilities, as if there were currently no existing facilities. Second, the Stochastic Multi-criteria Acceptability Analysis-TRI (SMAA-TRI) method is used to select the best suitable places for service centres among the existing facilities. It is noted that the application of mathematical programming model and SMAA-TRI integration approach on facility location problem is the first study in literature. Compression of outcomes shows that mixed integer linear programming (MILP) model tries to open facilities in districts which are favoured by SMAA-TRI solution.

scholarly journals Storage Allocation in Automated Container Terminals: the Upper Level

2016 ◽  
Vol 23 (s1) ◽  
pp. 160-174 ◽  
Author(s):  
Xia Mengjue ◽  
Zhao Ning ◽  
Mi Weijian
Keyword(s):  
Programming Model ◽  
Level Structure ◽  
Pso Algorithm ◽  
Container Terminals ◽  
Mixed Integer ◽  
Future Research ◽  
Storage Allocation ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Upper Level

Abstract Nowadays automation is a trend of container terminals all over the world. Although not applied in current automated container terminals, storage allocation is indispensable in conventional container terminals, and promising for automated container terminals in future. This paper seeks into the storage allocation problem in automated container terminals and proposed a two level structure for the problem. A mixed integer programming model is built for the upper level, and a modified Particle Swarm Optimization (PSO) algorithm is applied to solve the model. The applicable conditions of the model is investigated by numerical experiments, so as the performance of the algorithm in different problem scales. It is left to future research the lower level of the problem and the potential benefit of storage allocation to automated container terminals.

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