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Tato práce pojednává o analýze nákladů na logistiku společnosti provozující síť výdejních automatů a následné minimalizaci těchto nákladů změnou lokací a počtu zásobovacích dep. Nejprve je stanovena funkce reflektující závislost nákladů na dopravu, skladování a držení zásob na počtu a lokacích zásobovacích dep. Koeficienty této účelové funkce jsou určeny na základě dat poskytnutých zkoumanou firmou. Optimalizace rozmístění a počtu zásobovacích dep probíhá za pomoci iterativního algoritmu Nelder and Mead v kombinaci s aglomerativním shlukováním. Navržený přístup k optimalizaci logistické sítě je v práci popsán jak z matematicko-statistického hlediska, tak i z hlediska implementačního. Speciální pozornost je věnována hledání optimálních tras mezi zásobovacím depem a výdejními automaty pomocí geografického programu, který umožňuje měření délky trasy a času potřebného na ujetí stanovené vzdálenosti. V práci je poté rozebráno šest návrhů reorganizace logistické sítě, které reflektují optimální rozložení zásobovacích dep při jejich různém počtu. Rovněž jsou uváženy různé tvary funkce popisující náklady na držení zásob a je diskutován jejich vliv na optimální počet a lokace zásobovacích dep., This thesis discusses the analysis of logistics costs for a company operating a network of vending machines and the subsequent minimization of the established costs by changing the locations and number of supply depots. A function reflecting the dependence of transport, warehousing, and inventory holding costs on the number and locations of depots is derived. The coefficients of this objective function are identified based on data provided by the analyzed company. Optimization of the locations and number of supply depots is performed using the Nelder and Mead iterative algorithm in combination with agglomerative clustering. The proposed approach to optimizing the logistics network is described from a mathematical-statistical and implementation perspective. Special attention is paid to finding optimal routes between supply depots and vending machines using geographic software, which also allows for measuring the route length and the time required to cover the obtained distance. The thesis then presents six proposals for reorganizing the logistics network, reflecting the optimal distribution of supply depots at their different numbers. Various shapes of the inventory holding costs are also considered, and their impact on the optimal number and locations of supply depots is discussed.

Supply Chain Optimization (SCO) problem under uncertainty can be modeled as two-stage optimization problem where first-stage decisions are associated with design and development of facilities and second-stage decisions are associated with operation of the supply chain network. Recently, a robust scenario approach combing the traditional scenario or robust approach has been developed to better address uncertainties in SCO problems, and it can ensure solution feasibility and better expected objective value. But this approach can only address uncertainties bounded with the infinity-norm. This thesis proposes a modified robust scenario approach, which can be used to address uncertainty region bounded with the p-norm in SCO. In this case, after the normalization of the uncertainty region, the smallest box uncertainty region, that covers the normalized uncertainty region, can be partitioned into a number of box uncertainty subregions. Following some screening criteria, two subsets of the subregions that over-estimates and under-estimates the original uncertainty region can be selected. When the number of scenarios increases, the optimal objective values of the two robust scenario formulations converge to a constant, which is a good estimate of the true optimal value. This new robust scenario approach is then extended for any bounded uncertainty regions, in the context of robust optimization. In many industrial problem, the historical realizations of uncertain parameters are known. This thesis gives a preliminary discussion on a data driven robust scenario approach, where the available data are normalized and a reference box that covers the data with a certain confidence is constructed. Then, the reference box is partitioned into box-shaped uncertainty subregions. The benefits of the proposed robust scenario approach are demonstrated through some simple examples as well as an industrial SCO problem. The approach requires the solution of large-scale optimization problems wh, Thesis (Master, Chemical Engineering) -- Queen's University, 2015-11-19 16:46:06.148

Between the years of 2000 and 2012, natural disasters caused 1.7 trillion dollars in damage and affected 2.9 billion people (dosomething.org). In Americas (ranked second globally in terms of natural disasters) between 2007 and 2016, disasters caused 255,033 deaths, 898,816 injuries and damages worth $470 billion (Disasters, 2017). In 2016 alone, natural disasters caused $175 billion in damage with 8,700 lives (Munich RE, 2017). The above numbers reflect the amount of physical destruction only but do not include indirect losses such as unemployment, environmental consequences, and business disruptions. Therefore, the full impact of these catastrophic events is much greater than these numbers suggest. Response to and management of disaster relief supply chain is different from that of commercial supply chain/logistics in many aspects. Since humanitarian relief efforts depend to a large extent on international donors and the donors usually respond well to emergency, a well thought out long term strategic plan to relive human suffering is not well established. But studies indicate that investment in the planning stage of humanitarian supply chain is much more effective and saves many lives than spending on the operation side of relief efforts. This paper explores alternative ways to respond and manage humanitarian relief efforts utilizing the principles of commercial supply chain. More specifically, this paper addresses/outlines the process to improve relief outcomes by investing in the prepared stage of humanitarian supply chain.

Tato práce pojednává o analýze nákladů na logistiku společnosti provozující síť výdejních automatů a následné minimalizaci těchto nákladů změnou lokací a počtu zásobovacích dep. Nejprve je stanovena funkce reflektující závislost nákladů na dopravu, skladování a držení zásob na počtu a lokacích zásobovacích dep. Koeficienty této účelové funkce jsou určeny na základě dat poskytnutých zkoumanou firmou. Optimalizace rozmístění a počtu zásobovacích dep probíhá za pomoci iterativního algoritmu Nelder and Mead v kombinaci s aglomerativním shlukováním. Navržený přístup k optimalizaci logistické sítě je v práci popsán jak z matematicko-statistického hlediska, tak i z hlediska implementačního. Speciální pozornost je věnována hledání optimálních tras mezi zásobovacím depem a výdejními automaty pomocí geografického programu, který umožňuje měření délky trasy a času potřebného na ujetí stanovené vzdálenosti. V práci je poté rozebráno šest návrhů reorganizace logistické sítě, které reflektují optimální rozložení zásobovacích dep při jejich různém počtu. Rovněž jsou uváženy různé tvary funkce popisující náklady na držení zásob a je diskutován jejich vliv na optimální počet a lokace zásobovacích dep., This thesis discusses the analysis of logistics costs for a company operating a network of vending machines and the subsequent minimization of the established costs by changing the locations and number of supply depots. A function reflecting the dependence of transport, warehousing, and inventory holding costs on the number and locations of depots is derived. The coefficients of this objective function are identified based on data provided by the analyzed company. Optimization of the locations and number of supply depots is performed using the Nelder and Mead iterative algorithm in combination with agglomerative clustering. The proposed approach to optimizing the logistics network is described from a mathematical-statistical and implementation perspective. Special attention is paid to finding optimal routes between supply depots and vending machines using geographic software, which also allows for measuring the route length and the time required to cover the obtained distance. The thesis then presents six proposals for reorganizing the logistics network, reflecting the optimal distribution of supply depots at their different numbers. Various shapes of the inventory holding costs are also considered, and their impact on the optimal number and locations of supply depots is discussed.