Managing Supply for Construction Project with Uncertain Starting Date

There is a growing interest in supply management systems ¬¬in today’s competitive business environment. Importance of implementing supply management systems especially in home construction industry is due to the fact that several risks arising from different sources can adversely affect the project financially or its timely completion. Some risks of construction projects are out of managers’ control while other risks such as supply related ones can usually be controlled and directed by effective managerial tactics. In this thesis, we address the supplier selection problem (SSP) in wood-base construction projects in the presence of project commencement uncertainties. The project could be delayed for any reason and thus materials required for the project may not be needed on the promised date, however, pursuing the supplier for new delivery date may not be easy and without risk. Accepting the delivery before the project commencement date will be again a costly option because of the high holding cost. In this thesis, we present two problem cases and present heuristic based solution approaches. In the first case we assume that price of the product increases with the delay. In the second case we assume that promised quantity at the agreed price reduces with the delay. The proposed approaches are tested on the randomly generated data set and compared with the optimal solutions. The problems considered in this research are novel and the proposed approaches deal with the important and common risks in construction industry in order to achieve a robust supply chain. The solution approaches presented in this thesis can be applied to different industries to improve the quality and efficiency of supplier-buyer collaborations

Forest management-consideration of multiple objectives

In Canada, as a major forested country, forest resources provide significant environmental, social, and economic values. Hence, consideration of multiple often-conflicting criteria in forest management planning has become a necessity rather than a special case. Since 2013, a new forest management regime came to effect in the province of Quebec, Canada where the Ministry of Forests, Fauna, and Parks (MFFP) became responsible for preparing and implementing integrated forest development plans. In order for the MFFP to take local needs and goals into account usually multiple objectives need to be targeted. So, the main objective of this thesis is to analyze and to propose new business models for forest management planning addressing several key factors. The first part of the thesis includes a review of a number of planning methods and decision support systems for tactical decisions in the forest-based value creation network. In the second part of the thesis, we have proposed a multi-objective optimization model for the problem of selection of harvest areas and allocation of timber to wood-processing mills over 5-year planning horizon. This model has been used to analyze a tactical forest management plan in Quebec. The forest management unit 07451 inside region 7, Outaouais in western Québec was considered as our case study. The solution of the proposed multi-objective model was compared with the traditional cost minimization strategy. Also, the impacts of logistics constraints were assessed. Finally, in the third part of the thesis we have proposed a planning support tool to group the harvest areas in a way that the spatial dispersion of the clusters is reduced, meaning the logistics of moving the machinery between areas in each cluster becomes more efficient. The results from the three parts of the thesis have demonstrated that simultaneous consideration of some important objectives in the tactical forest management could lead to a more balanced and economically sustainable plan, in addition systematical cluterization of harvest areas will reduce the spatial dispersion of the harvest areas that a typical harvesting team has to cut, which consequently reduce the time and cost of movement of harvesting machineries among the areas for the team. In general, the work in this thesis can support an efficient forest management plan considering multiple objectives and minimizing the spatial dispersion of harvest areas that a harvesting team would cut. The optimization models and approaches proposed in this thesis are novel and practical for the forest management planning problems

Wood-based construction project supplier selection under uncertain starting date

There is a growing interest in supply management systems in today's competitive business environment. Importance of implementing supply management systems especially in home construction industry is due to the fact that several risks arising from different sources can adversely affect the project financially or its timely completion. Some risks of construction projects are out of managers' control while other risks such as supply related ones can usually be controlled and directed by effective managerial tactics. In this paper, we address the supplier selection problem (SSP) in wood-based construction industry (housing projects) in the presence of project commencement uncertainties. Based on the suppliers' (vendors') reaction towards these uncertainties in the delivery time, we explore two cases: (a) supplier selection with buyer penalty for a delay (SSPD) where the price of product increases with the delay; (b) supplier selection with quantity reduction for a buyer delay (SSQRD). Three heuristic-based supplier selection approaches are proposed and tested on randomly generated data sets. The proposed approaches show promising result

Development of an economically sustainable and balanced tactical forest management plan: a case study in Québec

In Canada, most of the forests are publicly owned and forest products companies depend on timber licenses issued by the provincial governments for their wood supplies. According to the Sustainable Forest Development Act effective in the province of QuĂŠbec since April 2013, the government is responsible for harvest area selection and timber allocation to companies. This is a complex tactical planning decision, with important impacts on downstream economic activities. Moreover, in order to avoid high-grading of forest resources and to determine a sustainable tactical plan which ensures a stable level of availability, quality and cost of supply over several years, it is necessary to simultaneously take these criteria into consideration during the planning process. We propose a mixed-integer nonlinear goal-programming formulation while employing Nadir theory as a reliable scaling technique to model this multi-objective planning problem. The model is solved by a linearization approach for a real case in the province of QuĂŠbec. The proposed solution method enables us to obtain good-quality solutions for relatively large cases. Results show the proposed model outperforms conventional cost-minimization planning strategy by ensuring a more balanced use of wood supply and costs for all stakeholders over a longer period.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Integrated forest harvest planning and road-building model with consideration of economies of scale

We consider the problem of tactical forest management over a 5-year horizon with yearly periods. The main decisions made consider which harvest areas to cut in each period, the flow of timber from an area to each wood-processing mill to satisfy its annual demand, and which roads to build to access a harvest area not connected to the existing road network. The goal is to minimize the total transportation and road-building costs subject to budget limitations. To explore the benefits of economies of scale (EOS) in road construction, we incorporated this notion in the proposed model. Then, the efficiency of the obtained solution is compared with the model without EOS. The proposed model is a mixed-integer linear program, including several timber assortments and multiple periods. We validated the model for a realistic case in the context of the province of Quebec. The results demonstrate that consideration of EOS significantly reduces the total cost by about 5.3%. In the EOS solution, the road segments that are built every year are very concentrated in specific parts of the region, allowing a road-building company to take advantage of EOS. Moreover, this solution provides a much more efficient timber transportation plan.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Sourcing problem for construction industry

In construction projects, availability of required material at right time at the project site is crucial to complete the project on time and within the budget. The construction project could be delayed for several reasons and this may disrupt supplies. In this work we assume that enough supply may not be available on time if the project delayed excessively unless the project manager has special supply contracts with the suppliers. Usually suppliers react in two ways towards change in delivery dates; either they may increase the price or provide a limited quantity on the negotiated price. In this work we discuss both the cases and provide solution approaches. The efficiency of the approaches is verified using randomly generated data sets

Minimizing Spatial Dispersion of Forest Harvest Areas using Spectral Clustering and Set Covering Modelling

In recent years, inclusion of spatial considerations in forest operations management has attracted great attention of both researchers and practitioners. In the province of Quebec, Canada, forest product companies sub-contract harvesting operations to contractors. One of the challenges faced by the harvesting teams relates to moving the harvesting machineries between harvest areas, which is usually very costly and time consuming. So in order to facilitate these operations, we propose a planning support tool to group the harvest areas in a way that the spatial dispersion of the clusters is reduced. We employed the spectral clustering algorithm to generate many alternative clusters of a set of harvest areas based on their transportation distance from one another and their available timber volume. Afterwards, a set covering model is developed to choose the clusters corresponding to the least spatial dispersion and approximately equal volume of timber. The approach is tested in a real case in Quebec and the results of two versions of set covering model were compared and analyzed.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author