国内: 海外
分野: 物流・運輸
製品: Gurobi Optimizer
毎年コペンハーゲン空港(CPH)を通過して旅行する何百万の乗客はまず初めに、チェック-イン・カウンターを訪れます。わずか100の利用可能なチェック-イン・カウンターを、150以上もの航空会社が共用しています。どのカウンターをどの出発便のために使うかを決める問題は、空港機能にとって複雑であり重大な問題です。
コペンハーゲン空港は急速な成長を経験し、航空会社のニーズを満たすためにカウンター機能を最大限に活用してきました。それらの経験を経て、空港のCEOは空港運用チームに、既存のカウンターを更に活用するためのより良い方法を見つけるという課題に取り組ませました。
Gurobiは、いくつかの重要な役割を果たしてきました。
Gurobiでは簡単にC++ APIを使用でき、インタラクティブ・シェルがアイデアから素早くプロトタイプを作成することを、そして私達の問題の本質が正しいかを確かめるのを助けてくれます。
私達はそれをすべて私達自身で行い、そのプロセスの中でGurobiを使います。準備ができたらその結果を送り、スタッフはその働きを確認し、それから私達はそのモデルを改良する作業をします。
Gurobiがあれば、私達がアルゴリズムについて心配する必要はありません。私達は、データを入手し、モデルを構築し、それをGurobiに渡し、結果を得ます。予期した通り、私達側が対応するいくつかのモデリングで2,3の課題にぶち当たりました。しかし、Gurobiはどんな時でも極めて役立ってくれました。とても素早く私達の疑問に答え、手助けしてくれました。
Gurobiがあれば、必要な時に規模を拡大できることを私達は知っています。改良した結果を提供し続け、ビジネスニーズの変化に対応し続けるために更なる複雑性を追加しソリューションのスペースを拡大することで、私達は時間をかけてモデルを強化してきました。私達が構築したかったモデルでGurobiが解くことが出来なかったモデルに、私達はまだ遭遇していません。
運用部署から来た複数のアナリストが一つのチームとして統合された2009年に、ORグループが始動しました。2013年、そのチームは7名で構成されていて、そのうちの5人がオペレーションズ・リサーチ分野の理学修士を持っています。Gurobiの購入以外のその他すべてのことは、社内で賄われています。私達が良い結果を確認した後、私達は私達のプロトタイプを置き換えるべきシステムを供給可能なプロバイダーを探し始めます。
空港のORチームは、その問題を最適化問題として見極め、最適化モデルを構築しました。彼らの次のステップは、このモデルを素早く解くことが出来るソルバーを見つけることでした。
複数の選択肢を比較した後、彼らは、そのモデルをGurobi C++ APIを使って実装しながら最初のプロトタイプのためにGurobiを選択しました。そのモデルの困難さについていくつか懸念があったにも関わらず、彼らは、Gurobiがそのモデルをかなり早く解くことが出来ることを見つけ、それにより、付加的な細部も付け加えることができるようになりました。例えば、彼らは、各航空会社が近くにある複数の同じカウンターの使用を続けるようにするという目標に時間をかけて取り組みました。この追加された詳細な内容が、実際にはモデルを解く難しさをなくし同時に、航空会社、チェック-イン業務を担当するスタッフ、そして乗客にとってより良いチェック-イン・カウンターの割り当ての結果をもたらしました。
空港にいるオペレーションズ・リサーチ( OR )のアナリストは、キャンディ屋にいる子供のようなものです。
つまり、潜在的な最適化問題に囲まれているのです。
— Tor Justesen 氏 オペレーション・アナリスト
既存のチェック-イン・カウンターの著しい使用率向上の結果、コペンハーゲン空港は、既存のカウンターで継続的な成長に対応することが出来ました。これにより、160万U.S.ドルを超えるチェック-イン設備への投資を先延ばしすることが可能になりました。
時間をかけて最適化の利点を人々が目にするにつれ、このチームは、コスト要因(例えば、更にカウンターを作ること)と利便性要因(例えば、航空会社が同様のカウンターを使い続けること)の間のトレードオフを試みることが出来ました。導入された最適化ソリューションにより、空港が新しいカウンターへの控えめな投資だけで大幅に旅客数を増加させることを可能にしたことをこの試みが更に証明をしました。
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