Quantifying the Bullwhip Effect in a Reverse Supply Chain: The Impact of Different Forecasting Methods

<div>The influence of <svg height="6.1673pt" id="M153" style="vertical-align:-0.2063904pt" version="1.1" viewbox="-0.0498162 -5.96091 7.51131 6.1673" width="7.51131pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M545 106L524 126C493 85 467 65 455 65C438 65 427 113 405 238C448 295 498 362 543 439L533 448L478 435C453 386 423 331 398 295H395C370 404 347 448 282 448C169 448 23 309 23 153C23 54 65 -12 128 -12C203 -12 283 70 339 155H341C360 29 380 -12 411 -12C444 -12 491 11 545 106ZM333 204C265 95 210 54 169 54C137 54 113 96 113 171C113 302 191 405 252 405C301 405 318 306 333 204Z"></path></g></svg> on the BE using the ES forecasting technique for different <span class="nowrap"><svg height="9.49473pt" id="M154" style="vertical-align:-0.2063999pt" version="1.1" viewbox="-0.0498162 -9.28833 3.60972 9.49473" width="3.60972pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M238 681C243 705 239 712 230 712C217 712 156 682 75 674L70 648H105C148 648 153 641 144 598L39 110C18 11 35 -12 55 -12C90 -12 166 36 221 103L205 125C174 93 130 65 118 65C112 65 108 68 114 96L238 681Z"></path></g></svg>.</span></div>

Mathematical Problems in Engineering

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Figure 8

Figure 8: Quantifying the Bullwhip Effect in a Reverse Supply Chain: The Impact of Different Forecasting Methods 