scholarly journals Stowage Planning in Multiple Ports with Shifting Fee Minimization

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
E. Zhang ◽  
Qihuang Mei ◽  
Ming Liu ◽  
Feifeng Zheng
Keyword(s):  
Turnaround Time ◽  
Mixed Integer ◽  
Container Port ◽  
Improved Genetic Algorithm ◽  
Mip Model ◽  
Stowage Planning ◽  
Port Transportation ◽  
Destination Port ◽  
Np Hardness ◽  
Transportation Route

This paper studies the problem of stowage planning within a vessel bay in a multiple port transportation route, aiming at minimizing the total container shifting fee. Since the access to containers is in the top-to-bottom order for each stack, reshuffle operations occur when a target container to be unloaded at its destination port is not stowed on the top of a stack at the time. Each container shift via a quay crane induces one unit of shifting fee that depends on the charge policy of the local container port. Previous studies assume that each container shift consumes a uniform cost in all ports and thus focus on minimizing the total number of shifts or the turnaround time of the vessel. Motivated by the observation that different ports are of nonuniform fee for each container shift, we propose a mixed integer programming (MIP) model for the problem to produce an optimal stowage planning with minimum total shifting fee in this work. Moreover, as the considered problem is NP-hard due to the NP-hardness of its counterpart with uniform unit shifting fee, we propose an improved genetic algorithm to solve the problem. The efficiency of the proposed algorithm is demonstrated via numerical experiments.

scholarly journals Cable tree wiring - benchmarking solvers on a real-world scheduling problem with a variety of precedence constraints

Constraints ◽  
2021 ◽  
Author(s):  
Jana Koehler ◽  
Josef Bürgler ◽  
Urs Fontana ◽  
Etienne Fux ◽  
Florian Herzog ◽  
...  
Keyword(s):  
State Of The Art ◽  
Precedence Constraints ◽  
Traveling Salesman ◽  
Mixed Integer ◽  
Automated Manufacturing ◽  
Scheduling Problem ◽  
Tasks Scheduling ◽  
Optimization Modulo Theories ◽  
Coupled Tasks ◽  
Np Hardness

AbstractCable trees are used in industrial products to transmit energy and information between different product parts. To this date, they are mostly assembled by humans and only few automated manufacturing solutions exist using complex robotic machines. For these machines, the wiring plan has to be translated into a wiring sequence of cable plugging operations to be followed by the machine. In this paper, we study and formalize the problem of deriving the optimal wiring sequence for a given layout of a cable tree. We summarize our investigations to model this cable tree wiring problem (CTW). as a traveling salesman problem with atomic, soft atomic, and disjunctive precedence constraints as well as tour-dependent edge costs such that it can be solved by state-of-the-art constraint programming (CP), Optimization Modulo Theories (OMT), and mixed-integer programming (MIP). solvers. It is further shown, how the CTW problem can be viewed as a soft version of the coupled tasks scheduling problem. We discuss various modeling variants for the problem, prove its NP-hardness, and empirically compare CP, OMT, and MIP solvers on a benchmark set of 278 instances. The complete benchmark set with all models and instance data is available on github and was included in the MiniZinc challenge 2020.

A high performance scalable fuzzy based modified Asymmetric Heterogene Multiprocessor System on Chip (AHt-MPSOC) reconfigurable architecture

2021 ◽  
pp. 1-12
Author(s):  
Arun Prasath Raveendran ◽  
Jafar A. Alzubi ◽  
Ramesh Sekaran ◽  
Manikandan Ramachandran
Keyword(s):  
High Performance ◽  
Standard Technique ◽  
System On Chip ◽  
Mixed Integer ◽  
Multiprocessor System ◽  
Compound System ◽  
Available Bandwidth ◽  
Mip Model ◽  
Fpga Chip ◽  
On Chip

This Ensuing generation of FPGA circuit tolerates the combination of lot of hard and soft cores as well as devoted accelerators on a chip. The Heterogene Multi-Processor System-on-Chip (Ht-MPSoC) architecture accomplishes the requirement of modern applications. A compound System on Chip (SoC) system designed for single FPGA chip, and that considered for the performance/power consumption ratio. In the existing method, a FPGA based Mixed Integer Programming (MIP) model used to define the Ht-MPSoC configuration by taking into consideration the sharing hardware accelerator between the cores. However, here, the sharing method differs from one processor to another based on FPGA architecture. Hence, high number of hardware resources on a single FPGA chip with low latency and power targeted. For this reason, a fuzzy based MIP and Graph theory based Traffic Estimator (GTE) are proposed system used to define New asymmetric multiprocessor heterogene framework on microprocessor (AHt-MPSoC) architecture. The bandwidths, energy consumption, wait and transmission range are better accomplished in this suggested technique than the standard technique and it is also implemented with a multi-task framework. The new Fuzzy control-based AHt-MPSoC analysis proves significant improvement of 14.7 percent in available bandwidth and 89.8 percent of energy minimized to various traffic scenarios as compared to conventional method.

Kiln Drying Operations Scheduling with Dynamic Composition of Loading Patterns

2021 ◽  
Vol 71 (2) ◽  
pp. 101-110
Author(s):  
Philippe Marier ◽  
Jonathan Gaudreault ◽  
Thomas Noguer
Keyword(s):  
Physical Stability ◽  
Difficult Problem ◽  
Mixed Integer ◽  
Planning And Scheduling ◽  
Operations Planning ◽  
Kiln Drying ◽  
Dynamic Composition ◽  
Mip Model ◽  
Loading Patterns ◽  
Lumber Drying

Abstract Planning and scheduling wood lumber drying operations is a very difficult problem. The literature proposes different methods aiming to minimize order lateness. They all make use of pre-established kiln loading patterns that are known to offer good physical stability in the kiln and allow full kiln space utilization. Instead, we propose a mixed integer programming (MIP) model, which can be used to generate loading patterns “on the fly.” This MIP model can be integrated into existing kiln drying operation planning/scheduling systems in order to improve their solutions. We show how this integration can be done by adapting a state of the art drying operations planning and scheduling methodology from the literature. We compare the solutions obtained by this system using the predefined loading patterns versus the solutions it generates if it is connected to our loading patterns generator MIP model. The study shows it is much better to dynamically create loading patterns than to use predefined ones, as most North American sawmills do.

A note on bi-objective optimization for sustainable supply chain network design in omnichannel

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Weidong Lei ◽  
Dandan Ke ◽  
Pengyu Yan ◽  
Jinsuo Zhang ◽  
Jinhang Li
Keyword(s):  
Mixed Integer ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Content Type ◽  
Product Flow ◽  
Flow Balance ◽  
Mip Model ◽  
Milp Model ◽  
Facility Capacity

PurposeThis paper aims to correct the existing mixed integer programming (MIP) model proposed by Yadav et al. (2019) [“Bi-objective optimization for sustainable supply chain network design in omnichannel.”, Journal of Manufacturing Technology Management, Vol. 30 No. 6, pp. 972–986].Design/methodology/approachThis paper first presents a counterexample to show that the existing MIP model is incorrect and then proposes an improved mixed integer linear programming (MILP) model for the considered problem. Last, a numerical experiment is conducted to test our improved MILP model.FindingsThis paper demonstrates that the formulations of the facility capacity constraints and the product flow balance constraints in the existing MIP model are incorrect and incomplete. Due to this reason, infeasible solutions could be identified as feasible ones by the existing MIP model. Hence, the optimal solution obtained with the existing MIP model could be infeasible. A counter-example is used to verify our observations. Computational results verify the effectiveness of our improved MILP model.Originality/valueThis paper gives a complete and correct formulation of the facility capacity constraints and the product flow balance constraints, and conducts other improvements on the existing MIP model. The improved MILP model can be easily implemented and would help companies to have more effective distribution networks under the omnichannel environment.

Production and Inter-Facility Transportation with Shipment Size Restrictions

2013 ◽  
pp. 74-92
Author(s):  
Mohamed K. Omar
Keyword(s):  
Integer Programming ◽  
Transportation Problem ◽  
Mixed Integer ◽  
Actual Performance ◽  
Industrial Data ◽  
Chemical Company ◽  
Mip Model ◽  
Proposed Model ◽  
Production Inventory ◽  
End Products

This chapter studies production and transportation problem confronting a speciality chemical company that has two manufacturing facilities. Facility I produces intermediate products which are then transported to Facility II where the end products are to be manufactured to meet customers’ demand. The author formulated the problem as a mixed integer programming (MIP) model that integrates the production and transportation decisions between the two facilities. The developed MIP aims to minimize the production, inventory, manpower, and transportation costs. Real industrial data are used to test and validate the developed MIP model. Comparing the model’s results and the company’s actual performance indicate that, if the company implemented the proposed model, significant costs savings could be achieved.

scholarly journals A Hybrid Personnel Scheduling Model for Staff Rostering Problems

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1702
Author(s):  
Jiun-Yan Shiau ◽  
Ming-Kung Huang ◽  
Chu-Yi Huang
Keyword(s):  
Airline Industry ◽  
Real Life ◽  
Integrated Approach ◽  
Manpower Planning ◽  
Mixed Integer ◽  
Aviation Industry ◽  
Personnel Scheduling ◽  
Staff Scheduling ◽  
Mip Model

The problem of staff scheduling in the airline industry is extensively investigated in operational research studies because efficient staff employment can drastically reduce the operational costs of airline companies. Considering the flight schedule of an airline company, staff scheduling is the process of assigning all necessary staff members in such a way that the airline can operate all its flights and construct a roster line for each employee while minimizing the corresponding overall costs for the personnel. This research uses a rostering case study of the ground staff in the aviation industry as an example to illustrate the application of integrating monthly and daily schedules. The ground staff in the aviation industry case is a rostering problem that includes three different types of personnel scheduling results: fluctuation-centered, mobility-centered, and project-centered planning. This paper presents an integrated mixed integer programming (MIP) model for determining the manpower requirements and related personnel shift designs for the ground staff at the airline to minimize manpower costs. The aim of this study is to complete the planning of the monthly and daily schedules simultaneously. A case study based on real-life data shows that this model is useful for the manpower planning of ground services at the airline and that the integrated approach is superior to the traditional two-stage approach.

scholarly journals An adaptive large neighborhood search heuristic for the planar storage location assignment problem: application to stowage planning for Roll-on Roll-off ships

2020 ◽  
Vol 26 (6) ◽  
pp. 885-912
Author(s):  
Jone R. Hansen ◽  
Kjetil Fagerholt ◽  
Magnus Stålhane ◽  
Jørgen G. Rakke
Keyword(s):  
Programming Model ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Large Neighborhood Search ◽  
Network Graph ◽  
Adaptive Large Neighborhood Search ◽  
Large Neighborhood ◽  
Storage Location ◽  
Stowage Planning ◽  
Stowage Plan

Abstract This paper considers a generalized version of the planar storage location problem arising in the stowage planning for Roll-on/Roll-off ships. A ship is set to sail along a predefined voyage where given cargoes are to be transported between different port pairs along the voyage. We aim at determining the optimal stowage plan for the vehicles stored on a deck of the ship so that the time spent moving vehicles to enable loading or unloading of other vehicles (shifting), is minimized. We propose a novel mixed integer programming model for the problem, considering both the stowage and shifting aspect of the problem. An adaptive large neighborhood search (ALNS) heuristic with several new destroy and repair operators is developed. We further show how the shifting cost can be effectively evaluated using Dijkstra’s algorithm by transforming the stowage plan into a network graph. The computational results show that the ALNS heuristic provides high quality solutions to realistic test instances.

Optimization Methods for Lot-Sizing Problem in an Automated Foundry

2013 ◽  
Vol 58 (3) ◽  
pp. 863-866 ◽  
Author(s):  
J. Duda ◽  
A. Stawowy
Keyword(s):  
Production Planning ◽  
Lot Sizing ◽  
Planning Horizon ◽  
Optimization Methods ◽  
Mixed Integer ◽  
Planning Problem ◽  
Lot Size ◽  
Mip Model ◽  
Production Planning Problem ◽  
Problem Instances

Abstract In the paper we studied a production planning problem in a mid-size foundry that provides tailor-made cast products in small lots for a large number of clients. Assuming that a production bottleneck is the furnace, a mixed-integer programming (MIP) model is proposed to determine the lot size of the items and the required alloys to be produced during each period of the finite planning horizon that is subdivided into smaller periods. As using an advanced commercial MIP solvers may be impractical for more complex and large problem instances, we proposed and compared a few computational intelligence heuristics i.e. tabu search, genetic algorithm and differential evolution. The examination showed that heuristic approaches can provide a good compromise between speed and quality of solutions and can be used in real-world production planning.

An optimization model for locating fuel treatments across a landscape to reduce expected fire losses

2008 ◽  
Vol 38 (4) ◽  
pp. 868-877 ◽  
Author(s):  
Yu Wei ◽  
Douglas Rideout ◽  
Andy Kirsch
Keyword(s):  
Spatial Information ◽  
Solution Process ◽  
Fire Risk ◽  
Simulation Models ◽  
Mixed Integer ◽  
Fire Intensity ◽  
Fuel Treatments ◽  
Fuel Treatment ◽  
Mip Model ◽  
Fire Ignition

Locating fuel treatments with scarce resources is an important consideration in landscape-level fuel management. This paper developed a mixed integer programming (MIP) model for allocating fuel treatments across a landscape based on spatial information for fire ignition risk, conditional probabilities of fire spread between raster cells, fire intensity levels, and values at risk. The fire ignition risk in each raster cell is defined as the probability of fire burning a cell because of the ignition within that cell. The conditional probability that fire would spread between adjacent cells A and B is defined as the probability of a fire spreading into cell B after burning in cell A. This model locates fuel treatments by using a fire risk distribution map calculated through fire simulation models. Fire risk is assumed to accumulate across a landscape following major wind directions and the MIP model locates fuel treatments to efficiently break this pattern of fire risk accumulation. Fuel treatment resources are scarce and such scarcity is introduced through a budget constraint. A test case is designed based on a portion of the landscape (15 552 ha) within the Southern Sierra fire planning unit to demonstrate the data requirements, solution process, and model results. Fuel treatment schedules, based upon single and dual wind directions, are compared.

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